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<title>Negativity Biases and Political Ideology: A Comparative Test Across 17 Countries, Replication File</title>

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) 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g5NLLIEXi8otcDQcUts0D8eQ1iVDRAMBTsYiNdRIxE09EIBJO9A2xqgERTaW86BUFn0OD2xFO97FAgFhF6OoQ7prYt4XwSeUgQHiJyDbeke9IdQntciLQ1FlJMaYcUNvZBg+FB1ubjlnRNvl3o6IEU2w7fdNPhm/hh+FLysUu6++DLHkOkrSHYEjH0tEPe7WdD3uyDgvAgK/m4szFFR7ch0toUgBTdWHr7EpaWru6+6dmbbnqWEbV2EtxAsXiZAPTtGPSbHsotI2leoM8TePEqgSQprs7AGFf8kuOkPdZPXGb55POAW1d/jLST9v5YflasP6v/CO7+GNAPC2BMZWmsOjp2NNbfHwMCJD+LPVL+D/OYlWEEI/9jpPddOFkB5d1GSuKZYggmCCd7JUxD7EXAzxyirYnNDLdDZoFdx14kivkvGc3579Jm36reTTvDgBnaO6vzyQ6chQmlsMoIkIQ2+bBDWBud1Va4pcCn8CPqxlh/fgtG8IPaPH8C5wk6/nZDv69jurV5QhtwE0x2iqOsj9Mx8B9/0EaUdiPfOYYDCi/q9jhWRuupMDEU0+CtX0sDFxv07T/K5niBPqN9+tQjgEc31NGCXFeMcCEuQBIc/BK4CO78u7EPYvl3yaEfK3vcb6qP1R2tI7vUjVDDUdKubsSrNjYKY1qBEa2P50SJoaXiksIoLiCwnxS6EBuBde87botNfdEWwYvF/R0/u5yCqhGeEOR2ynSeyXjt6ka7neyye8kryBSWE52y+RBgogrXPZ8E1yIHoHIFUM+AbJhE7lbMtt8ApL+xmZW7PwbjAO0fAVoXQOuiSP/ksIVdFZ0aulsamKUzwPZ/NYDMJRBPCxsBqLzqHyneXF6Ej9HlIFo7+pg+jUb3unRmGpstGkm6etOuDBGA5wCMefp1gTHcdZlvPBXlOslvYTp1cd8UjYLVd/J5awNrIOKLnIt9MD9qdrKrWCvA6ALm3QV9VrsPm60Q7+RHJHP+2hqfugo/MvI2H/mqr4b9tFnKSRY1Y5Ek80Nm/WIhr1ikKnxGz9TWXrokf9xwujfvcOTtNTWnxd0F37Y2W79tteBqZ4G5qLCuomw+nSr28QESCRVLTyYKILGJOPfcnaIFOsewhRdvv+rWa/Wih0vlbX6Zb75T5C0qNKVFvH1QL/vazSWgC2s6oWXXIuUxQelKiJbowuJDQViatLmLijg9CQBMg8WiPgiw3LEeYRmm5f+XdnvkDnxLLjMLxtvX74C3OlwPQqx4xwIdpPx38LrlDphiyWUWHWKAzzxurS/xTo+P5wGFak62ap1PVFFN4v/y+xuR39WnIO7lsWfwgVsK17wxrs9K8ltIKuhkw7f/6dhK6gQokFKhWX3urrjk/rnI0pgfpGMeuQIUaEM7+GF5q2iMkCaMQwxxOzcvU0eXbsnS9XknXvP7Gtw5dwPXlFu2ecvSHEZgNDsU6x/GdXBYXyOQjzZReSedeEPY6nEv9gJR4oBQJtFO6Kd0fwC6BO4LNHDeBujB6dSNcUQC9zIv2LnAzGk99bUDrdFY+9yGFQtEo0GQPNv6vS2drj4+1jHbv3aJSMUWP+QTZrmbNTjU8wyG/iXNNpskybLcJ3CiTF5Ir+JYzmJwE0mSVhlxbtbmvweB3ulB6Til5UuUZydpgiFVeobhU0WaBqpJ198d+/XeNRTZ9/1OPfG7+2hwzd5W3D+hmyjsRcUg/+Cavb++Vh2ls3L7zT/etOnHNxeerv313vzLVqPai4nJv+K1FC6040/4udw7sAb3laSg0XCkAAs0npBO6VJabS4Elk/U+D4gTXW+j0wnrMlqNamq4tMIYB87tE10i0FR3LZNhJsb7/R561btmes8YBCRkhYNByRtKd55mqTas9FYhJnbRGHuOh3M4QTdgQSqmgRxuzGdSvZGcbMxNQGk5C3ebLjoXIOFM4l+WKHmLTJwRv9E8GWJ6dYvf/FmEyEGr+gyrr1p5zrgkz0Cw2j94Hv8Jdx7dIVegBSNtgsqGsRQEYiIBoXwD0LNvQ5d7s5Z00QzwNhqZA0b+tMG1tQq5nd84uq8R0zPvX35G8uRaze4jcOHzz0w1+Q2BIRvf6J6Kgatnrbiem+CFvAxfkrndzD9MFPP1GWTUHclpASUkCNAQkpCCcCgDSUDAhDZ+CuEkgn8J7i9nMA7pA4lISappxILKfAeSAbIcSDuN2bJcfZILqeO5rLs0MnngSHYRdrHjmaz7JEsEPw51ZqDJDmUIOZIe34WaQeegNsJn1qz8AIpT3yCjyEih/xELkuJ0lEMYTLVCiWpo5oYMleMH6USyYJcD+uOe+kWKpn1Qns34iyYDjkSLvgnZXcgVQNeqINXr48m3iS7cjm8tedyY0f1QvTnHHdsrKby/+SSbPY8/NH6vpl/Esq3Ae4ZU1HC44KFiI9o7CEgab/RqHbj7s5KAg06s39ZP/zxI/mVuF/TbTSy+3Fb8If9/cv7+wt91yy8RfP1QXtW5RzQn7qIiZyuFM5QfJ5E9uVnqT85TanFx0lkP3ukBAMprvsRyi/C8NAJL1xbIIirSvnSj4O5netb4JxmNANHPssHAcHMHsFRgEug816gDBeMbdfiuRcghqYcm0+Xxx/5IAEtN3fqFF3LzAXqwoT0PN0OVTNqxo8sxMkd5Ig6k79Zk7VxxX6gMLOZFQgvpW2RrMW1D0BDihaXQ9wVRoBxPLfpknmkeMtoB/qM9cRc9IqmMD2XUmdZ7GSRKPUZvChf8BoykriM2MnKYbOHX8R7cLdNCxSFFVQqoYswnlWtlFS2mNkhswVpZiQW1J/UKFfipHGlUkM6UKBhMz1istELIHJLMSctu3ugzfaVSOjKvUgc/THK4Sdg2Wscz69leKIkkrwuuWiOe9yGYKQXRumkC3qbRcMwrvhjNXgdZk3RxAUEhuSPvn3nnd++U/3vlVOmrJzCD8JLxV1OHRjrZifbcFDOuRNTGqdgQm1tSNJ2OcQ04YiEXuxtII1ECSQRoQGYioEsgCfchB4ghAtw7FfJre4WZ9hkVi9MtjuWqtdNDlpMrfEG9fOT6q21okg+e4As38MfGquNt7oUws6Ysarj1/efE+yst86YUVNvDdts3Pv5c8m/aP0C+f8/Qb+IMnGq09BgwN01oIOAnAdagI8mBSrqk1gxTDUBOtk2ousEtBH2z4Ir2d3f6k8PXXVlt2qN9RODxRuoJT/v27wm09jRYVc/e++iyx2tyzJb/n3J0htXP87eSsQaf2Ly0s6Zmxela88REy1cf4273mI3iXNJ7KxrZibOm9xm6rl4fqy/t27smU8tOfdW2ucBzg2UfmOIVyLIl3kpYlwphDISTXJXsctmiDtN7fNV6zelgxwnWxsVr83Aj/S5ki1jL/a0GC6+2L6Um+aoddlNFuj+bJ8mH/iaLh8I0/U51NspIEfq0dohwyFXKgm4NggwQ4rRhCOUFtxxo8XnitT4cnGfT93IS8FaT85XE3H5LMY4zIEPL1hw443wz+1UmhTJyJGxZzw+wsKkKZgUiVtKOKMEb2AKHTv61FNc01PQFwKnvsZ/9pPA4RKTASWahmh+8MxwzHxKy74IRn5LGRjsPUUwTu64UYNY38caqd7HKucZ/tHnODtENw/2UfHRMaq1UUPDJQ0OKkWCeet5fYOhII1VRz8+/Elg5j4Gxur3J8o2PJ4rg+2d08T/fwEzSVbyZ9XPro95T477lRKqUSRXQnauHNsISAl27oWi6Fv9z48JMv8r/aMMj8onCP/DuDZOuN+GPPr/+p7bx+7JlbYdppcNhzKU/1Px5aiaGDn/s1iGMaBcleKUo/v9rcxkZj7DBEKOfrayytXNLYiUdBY+pleQXdnscKlQcpzuWluxsieeyuXIK6SdxozitWyGOV3vOHHjguyCQ6fpIYy2JwvrQEF/Qa9Pdf/QqOSqCiE/EE1/XIVKTc2tzWbHnimrEd+Vyz311Ml3P0GVTj7PD5aDnsvCvH36alEaPMePcMegXs7x8igTu4B9v7G9vTHvhCu/kzIdx+BxC0ay9zRSvoS0F2lIxI+X7klU63I40gLQ3w5ep5na+SFnba3z5D64zv+QtM4n4ffG3tq4aNHGRfxgrXPMim+5487abL7xhdseIRn1KDl+7aINixdv0OD+JSPwKf5+xoP6aiTeQIDVlIhMcL1H5R9PYXvprs3fv2bO7MOplCmweuiq2JRZ1zz+9a/v2PH1Hfz9236w+ZrPXvWfAxlj4NLLHpq3c/PQ3uvmvbrjG7fe+o2y/cLdtE6VUlXi0ASb1VLUBVSUWSU4HdvAraTyS8xzM8NxvxFkXV6pUVRiJwcgC5zEeht4rwcp7ki0k41G0qlQhG1Vzlq8alEmnFi58caB5Q9vn988MLhqyVlHvLEWjtQFeupdiocF/tkkOGPW2ibWaBTkeZ/dvPWazXfOnnvL6jkRXpi85sFzZt+55ZptW3bl1cCCHZPD06MhySha7UFzjcjbp8fOecFCirzAG/yVjBX6OFIaadSjQq1nNhyIe8tVbaaSdHlXIWKacMeuZA1uxS95zILhyrxAdsXTL6m7kNQlx2P9uZf2qhufePFFbpI6/OU0WcP99RrCsrwseVot5mtytpf6Y0gm9sdeyKnPQ7onyK4nXlR/rg7H95M1upzu89DH6pgUcikoiihJ6NJKmRxV1x+MJiOA3YwhDRQrWU0u/0rvq0VYXnyCwsLeTJYBq3dAtJDavuzyoVpzZ99Z0+a0uoiFH/xcqgDR7rUFeOrUn6Cywb8ZeNMbhLV5ugP9l0zv9UN5b5mFkjzxUcpPJCn3V402pRxtJd2GrnLdhtVk9ZSZh9W91fCSH5B7ofxPiWL+j3D/uwhBRdyAyozeZwvQzs79soi+BKSnafLviZCcfrpBpLyimfLfTyJtbyruIQKD01tUwJyKEo/ybaxkSNFUMdMkhQoJyRBQFhnUkDQSXhTM+3NmY0EDM7ffLIjqWEGt8lCO6mLia3PukFnghosJD5p5SIho/VDkzQfLE+IrYoJXkD19pdP7OwG/voIUtagiWiZ4PAFTHHlTVhRZ7dYmPar+NJ+8JhmR6DFK5DV1foHoLNO/pHrvZfmWZ15RQlwvoVDKhCWNK3CCch9lfFBuAqUgpFSShmNaPj+i5++WZfKeViJfW5HnUakVL4UCNVkA4+ETfIqx4B5xSaP2L1yn0zn2ltPn4+OqZGmwwEVCaCSqG53ldtL1oLGAhdMLd09MpCCF6tD6ZnAZBY9hDaYsP0jzZ0j5ZjKsF4i1UmLuhbJMCnYJPt5VwFNvmZawXjEvLJqIH8STonZjq7BZ8gKgR20C9MDFqJAX1H64QW2NEup6qgzLP8cvppL/NNTOBTCJABOHeWoXzLhw4Wuy7gaBtjKr9kgKq8ZlRYBS32Lpxc8vIhpNDTfyNXWybMJbn2RyQ5EmWc2QF9wmSZ0KYCE+cPuYO6b15Uotj2Kd4MItLS7gtFbkTdrFND6pvEZqv5Yv7jXAus7Pg7avo7KDot50NX3CPkP+Kps8J9/3mGQIteY/LGPC+L7872SPR2br5fy8MtKBMHedGuM28/MZmPJMrGgi3Gb1S+Si1/L/zrZwO9XH1ce/z7ZQ1WSoY/+pMb5FT4ua0Wm+Jf/298nFmChEQ+Ti71est4mq9VYI6RsymoRJKYidElT2FGnDTZvqtfhGAFTbeqEw68GqtfmbVa/1IFO1/jdWr/8BDRRtQh9XNjubEm4aWVpVonpTGR7PVGc+KJNoBIWF7kYi4gUV3r1U6723i6TxUl3n3/tM27aZfKb7THiHW9VzFSwHJ05VfK6Ar7kaB0XgPPE0BSkSFKsBUpaLihEWoA9wBt8qirh2VSOkZwXEwyrxZ5jyt2rJmSo9gX7cg6jsEUGJU9z9xJPOEM3uQQxKgkh35DNATnVyrmJ3mbCNyIB/yox4wH1bg2DwN7q9kov4pFqny8oSm3RQbGgJ1QQTs6ZMLilOVYJ9v6Wha3HcJ9jddsXp9YhGUXLXt/qMDnvLpPNTXfNa60z5/yjXQOMq+lNmwh5egpYrdfZQZV9rI47xlRkuyTjpzsmCBSWNkAXVoK8sgYWqQJWbo1RLo6QH0YW6pxqfCnRgkd+RiFjUQUQ7poIaYoakgXxwFd9BuuI38H1xBxXSFb/pBDIKQFn7YB3dB36l7sG1FLaKiBdp1KxLvfswap/30lnVESgNnvjbUoT6w9N+Xoio0qcYOIM+heg940YimsucQVvli9NEcft2UZwGQwLuilj1fFr1i3NP94X+PE7Hpvtj6lBJfJ4R6NvWiaL6MgzWHxiN66DExa+dAdAbMYX6HVF8A+7rjEZIXAVbDe7PVI9rmN69JOLV1DOSvRPxWNPZBZf/Nf+Ny65BhYxxxV+77XJ2wfQ389/IQPgajXbwMsuAz/0IaQcXJavKbRqR2IqyZruXjVC2+hdee/5vdnYOedpmVtR3NGXldxSzDSIiBVpkGb9by89UpEPKrSLZmyFDzMab/wXl2CNe7s/qCtTvWgG5kpBmCBlSzDS/r8N4uwBwohRW63JTS1y32f0TQsPfXVGEHQrV8/NCfiOUVirYcBbIeA2+iF68rQIo3B/S628vYESr79ehzS7Q9LEL9UXmik9XVHb1yBO3Ngvt5935+k1efkV51mzzrM0LL3/20avnwMeKuWyOUZg2TasSqZ+KcZQiOn1Iu2Vh497ALUVZiCKt/gh6IvTIj1ZLRjWAkpHKOKovNwp00eqPROiAbiNEKieXwMLcXhVJ1/uzmLP4tfxaHR59cBdJVG1kTAgl9ze9QKUEQ946Hkb+okJ5JRDyf54Axur1D+WS49cLr0tTPEu7UmXrxcSr3XNvumv4yXzInXKH4F7Tc7p17Zt+t/qW2+93k063X7VW6lALxTY7i1nBXMxcxmzQbabxz+tJo+wijYaIGMNS8AoSMgAPt84DdHOoMPfjXhF+kuH1tZvuFQrRCN07xGcXRX9MYxYchDe5BcHj+Z4i+42WyPc8Xofi7bbZJN5nJLJ5qr6IqRtzqNlM17SpFsnkEyTWoABEjz4JXOQvzWYuwdnV5LNGOwTM5v9r4RpQ8ZXsYodks3o31JBlzbYtNotisnm22MxiwGFXam5oN1n0TA/hRvshvTSDwHff4nNzRo9Dum6PaJbMXzDz+x+Fkj4L4bFNBb1asqsgH7Dyh4DvbkPtf5yMDKzEwyoaESMSNS9P9gJVA3/RTlwoMwZvxECFWxIPNw9gi01nOHjP32esZTtmXHnxvZd8ZtakqQ7ekajbXetpNa6ocTVxJtY+uSe69OLz77zh5bDR3xjZMzUz6fxrz1nqrZGcHQHfPVefN+fiK86LeXj+Sc5lPKy+k/vCUI/DaLFYCWHr6nbXuILTIsb5imNKY/rCm28fSMxPhkN1XbNMNZGuqwOBhtTSxWuTk6bw0ZaG86b1hKddePOKuBvmiguYBn4T/yOqOyGRBt7bKUI1GjioBC8aUKwF7Q319UgcmtFGIzCJGBqwQij0ynDsfdFGc3TS3BlNfJ25xmzniMkpXXTPvCaD3ZaZvyzjmZdudBostmhb0ORZNN2sJBeed1HXkrUsywueQH+L0eCPxmsa5ZpgRJSDZ11yDv+jmbd86vxZfc1WcZJ3UkMq1BOOOVtvu/+pB+en186d3GTwWAw2jheaJs09/+LNfZft37DALyrNj1wABMuUKbODyTVnT/KYbJ3Tpq8IrNh92dkxOj5P/YpZx4/ycyiVcDYdn4JbEoKdQi9054iBKsygLW46FRGxAb0NPNCm8BSNCPjoKcj6EAus4SuP3rB+cV99/eTF6294dA8+TK6v74MHVpYNRt/I30e8QGTOOdfGWzzxcy+87a7bLjw37rHw1nPzp0KyyRSeZO+QQhInt3dYgvycjrPOv+T8s1rptaP84VeywdWX2T4ysr0/7TLIs6+x9zib56ye1dM9e/XsZmePY3NDs9zlnNVt4+WgHJbbz3Livg4P9WWgviOMm4kCRT6I8vw0NbUUEnFvOuFKoxQW1gTsvFirsF5pb7qTUCx4i7VmtToveaDxvK9uOaedVvPRpVOnNz0Q6bry7uiSdQ8t7Vy4JQKVS+XPplV2ts4bvCwZu+KzgITtxepaPRzWdpv74muvv6RO0SorX6cu/dqKn/XWnrtp/Zragz13DUCl5myiFW2Ycvb0PtsXnU+tx8pvLFbUspLX68mdegwmOif/NPDONajTGoUh6tU56HBJCTBASVvNUB5VIiKpc9kd7kludodSFz7xQbiOmMk5dOYk56gzL6uaf7N8a6MQOHm0ae6snZpFDfuT3/jdYzjzwkXXIVHoXNuCfQslQZqBZjTsoHMqrkE4jaYdgkGz2ATOgB3cPkSukD01DnV3ttb1wx+6arPqbkcNAHoFPzKUUQ+qL0k97pjbZv1I/egC9zTFbrrlFpNdmea+gIgfWW3wqkcis8ky5FAcRd1If5nNZrl2FFpungc8wpoCl1BpQV/ScS+zjlASyUTVv/AJ46gkJI4bHX4lTnloctxPZE1ckS3+jG2fKIjkQFyzuo8jvYQG1OrGvJPSTu/nSp9PHNTl4z5hK/8gtXVKF6gEKiglgcKiRlCESsQCV5QIlKWKpr34lt/wkSx/JCmP5/cBKQfl/5gd+rOS/+p91/+YCg5CXK2W4M9fu+/6xxX+vnelVuldIDCG0VQTpU9Dw4pRfei+6zWx0MLie0gPbyrkmRU7OwT16JGeyXLHqOLqAfVN1GPlBzWtFNzj0TRTCjogtP1NjIvu5habN5Aoa1k66wGpqriVetJgiGdwDZtKhnN0y4n9sXYnsqGmZfDSR15+5NLBlhoDaedEm7sxmpqRija6ZEEg2EAnTiAC8IrmFbGz1q08P9PSkjl/5bqzYqT9hMmptEXDgTqP3Wiye+sD4Wir4jCeoHbbp5hRfpB7BakUIppIlPCD30dR1GtslDz8OsqbXmejFC/v8wu5X2myq7SJ8Avzv9DFUJySf5uNvq4+Ti7W9D/OZrLChdwxmPNiBRqVjnpK/aGxRCDspVYKAW9AN1JANoo8wP4BJUlGqdgw6m1qPQ2QW3+OfU5/ieLS/NuKpDU3uf8bcAXyBal5jMR2NEAbPAZt0K3hvxHBEDlUxfIGcD+N2gNSNx36nfqlAYow0puatNpRz0e4W2oahKzQHsjf2c16ad/3t2KTtPobnX6D8C8pd0MDP+Kx7wnXqGGlLQcvikMErm6TmfsuxJXbSAxqNjOogJLQBLiKEHAE+JGTS3JoEhTrz8/CB+5YlupJ58aOat8Kv4JvregxwcU5Cp8GFAFm1FyOfto6GS2m1NGTS6CPNKkbsTdCBlnN9onMho55BX8IJZtEQ35lk+htwN5A0V3RCPoD/yXAcv6pAtbZczRUA64JmcUf4q7Q89ZHLeJVZ5D1Ps/t+0iCT3AHVtZC7JDCXfR7OSb/Xja5H3zQbZL1B+ULX1BMTEk3AseSpmnKEK4T9ekMIidUCRQFfcbj7z8gNLvzF7mbhQN8h6ZbRset+nQWdS/ZX3k7WpS8P9sfo0iGS64wV516pOhjI6TZ2dApgI5+LhxywYoWxKUrykKJsIoDsR4mSrCTg0egMPnLW/3Q5Nn8BZEuzqEI7HK3n0+zFmuO3TtWQ5WJoG9YqCD6Gc32SxnbnVPfsxvrFXK2dILl7bLthDp6glhcsfp4bYvbSmj/mQ94uBTw0E73x2jbNRCvC6VL6GCFDwU7eWQDcC5FY5s0slieRDwtAbRsbLXbaXAuu14e2OJw1dc6jQ3ZdY8v7rv2/BWZLqvFWVvvcmwZkK9f5jS4muO9yR5res4kfkRxhV03L1RfPOiPtYi8pd7jNEsOpyTwxpaY/yCZu/Amd5Or9uS3DYaeqVOhH7gZN/8I/wi1fEuLXvyNivibjuKvN+1Nc01HF/3h+ef/sOhox8MPd5SFucPjorQwXT+ytA8EmA5mamHNFDVhBI5pjZbQpugBNkO8MvRub8KVDKST1Wag7D3xlin1ZF7LFP/79nbvCXFOY+PUjrT7/otsPXXZ4exdPzuhZuL5LUXVAn7k7PbhG89uz3b41X01gbjP1xwlu5rrvvf9+pbs6E/Vu7Nk642/PYRaAiUBdrmO6CDTBLPQFA1ur0uXoBR1INDMkypKpoTqnSMx5GiEdTEaSHLs0Alvu/19/5QW9Rv1U1ridT22i+53pzumbs+XFFXYC++CGsTj5JUT/GCgRt3n78i2n71FHG4/u6X++9+raya7os3ZbDmgWfXun44e+u2NZKuGZ0HiF8M4TlMPR+EU6rPKRJ8wOU2RFUFLex3egEsz3YqEAq0cqhAAW19dBZIlVzR61tuIdTnpXH7l+uXrbjPUyep+8cl6aXKWhPHpDcXl9KiTWDNr4mBQc8Tq+NzK/OKSbsfl79o9G20R+brBXYvUg0rLHhtrc4TN81TTOWSZ0gL1ZVlOYH2ery/7XVUjFMbzYpg7UswcqJPQwBd0LKLabJ8IaCr2otcjSkIrGwootKECaUd4XH1+SdazRrfddkBU98t1htvWrbjqSqjaCguxrffM/5zDCpBALUycmajhd+R6ww4SWafuZ5eU+tPid4lgd3gt+b/Y9rQoZNmiXYPXyRHbRs8zX/f4WIFjWZJtUdSD55AP3xtXH+ZipC0EqdBGDA4CoYEU6gRLGPU11QhkLTBiEYPiqOeQgwTCl9aok1Qr5pFf71qEeNxjy/8F0GoqYPv75Yh9j3x4DuJ+uEzHRpAq2lMqb+qfTdiq6kGtzfOWsv0c7lSeMXDHBDe1MT+LUgx0Pg/p87u2UicdIvqQi8DkxhcUwUXCedMpb4NQjwY3npTmgsURJavLwCRyEcN2HfWsDVGfv/u9ZUWUx+PYFueUKwaNvbtu+Xps3eVWbN1GcgVrdMnWJ7WmJz9SD66EBidag0NF1Ukep0t5A7sFCWdhzvYwHv6L/BehXuHqfaBwBEU7hfVLcXvS4VQv+T/vaSIl7cbeMc7ekv9i8S3e1L5xxpvMGcu1EYPbKyCiijjGXcDKckm43PqU2qNWlXusZMiqF82cuVzolUHN9NNR0HZPxFPV9V0wLtvq+k4DqOwVWDlzuQLVdqFiP08cRX7aRlBVfR8cb55bWe5LExnlcsDp1vAP8Q9BucPMk1Ulh4GnN0SAdxcNHv3q9ohx1Ati4S/tkWjIDe3hQdkUGrGRaFBiUdiTSkI41UkMuuQHP+EaSQYlPQTFWJF03BNPpTu5KFAdkWgDukzsZKMG0Q1TAQQglScOaP/dsZ8+fP75D/9Uu5Gs3FY/2SxPld0DHOciXI9gqjcEidXjE+3BLosy0OcX3T7O5g65ROGyzQ2BZs7WbZVnO5ydLe32hMwTQ4wnnKXW6XW5LAa7oaXOIHoUl0FgLQLH2by8wSTWeAx2Y5PDazK3BqZbeJZwXGPaYhX87ZNszoDdaRxotXO1nNlpdvAPFWHDm8PqEE0sZxDEqGzxisFNnuCWetPcGrObN0p23tTZwMuRVodSV8+LTrOV3eRvzjQZiSjaLYS1WEJe0kNsJlZu9LFun7++wW4gRDRbaxw2nrOGm+xOj9cmtbp9ZqeTM1m8UXfQQCSTVSQox6pvtjot/FpHvIUjJovFEoYvHYV9C5Y/xN9OfcalvII37UEhTbTg/AQIaPb4Vz6j5u8/aViycMod/fkDcpu8QZbZoeBi/vbzP3XPsZvOubMtaPHkD9jt6+U2O7vqU/9C9SMvgrXpQNG/E0oJxun+CiElUa0IKQSUwERxOntKSV7ekcuh9VBZBBo3VUcB58ofKBHCwLyf9qFosz9Ibf8dGqwaBMjRig4SGOZ2UkWI7UiO9OfUPdxOYFApUZyfpY7mgEc5rtNGGk2H1lPhAk1Hp/VAMqQEHEUfEYkkUQq1JMdzsX7kklRrTrUi1wMcDjmu1YYfATj7Y+pGpPEBXuoQIj8rR9mgCl4C9yqmF7xnVWxGVniNqtpVmXBvQ6iwni5YQ8a1jYrXtc2J13HvgkvqWxuva1sbr+P2S5ceKGyBwDv2DbrToe1u6BkAJV7xnVLUaq0sJB8pFqcUIPi3yuwxi4JuLr+P30f3OkPQ72aO0xYo3/EsmO3QO5qEF8S0qQH0UsKXv0brnl9+8M7jF174+DsfvPOl1au/RL5/9DsbNnwHL2pHR1NTRxMZhJtHktOOxLxErPF6YlLvpC9YP73x+4ofw+3xVdrHcDE0dQQCmCRgvt9b35xINDf1CDcRSfJ+pYl+Sf8YcurfmXP5F/kj6J82jNsrkWiEuhVlgFfyNkB3S5MUzLhoNiwSCYcxQ7Ui4J0Xh7fmqRbaPa1tzujxkBRlsEHy0/OM4pYLPb7g9O6BQJN6l9zQ0OGyCaZz0vMTbHOzXfQ7a2tsterTcqxeInODoemdktw+1SbVhKwtW9ffe8VKadK0OVuC3bWzyKm5LeddsWTeorWyY9IMtUFutdu5g+Rn533qkocdvLs2HmhU75br/MmWtD8zA3OP2t1ea636jEzqYxJZGAwFiDEd61oTsrRuW3/3pYNi3bS+Rd+GjOfVpAPNd6y64Gsz1GaZleWIPoYL/v9mTeQBENVEguiF1aC4YeXxFETw6QyPfn0m9g8IrMFAvKM1EI11DARnbqibHk/Iojy5rSdgCyZi06y8sS024PeuO4MfwQ5Y9yKRZCqyYaF30vzeHlmUprR21tR0t0yz8KZY66zWuGvxVQB/36kP+K38t2Hu6NQ9SFJfw0AdpqPEK2qTMpf2VCqJwqPoJezTL824b8akoL+x03nhh+oNo5e77psxg9Q5LzebIKD+fsY34f2MtB9fk9v5b8PT6tYrgv4kRPwd0q9z3gdJSJ0653KjCYPwCaR5aUY63eW48O/kdo33yxX9wCiMv2QTrk8eGSI6Ag6moG9t2P/F7GRNlDjl0gw7pJ5aOXXqyqn8SENnXBmbSwUYLyqJjv3UmY1nKr4t80no0faXsaIEiF/BRaIBnItSce4OUif7W6Vm9T9H1X9Vj71BEm+RdmIJQST/ZfVdudUvh9S/qqNvqT98g9SQ3lHibZY0mRVHooyDN/FHmTgzjdozKw28NwQ0hwN6BCoPKaEk3YtKwNhwRLXuk076CGoZNXDQcRwZvreTZY9EZi+d0s4+ztv8iei04JQl6ZbDD2eHV7X4uHuFVfPrOmcs6m6Kr7hssr+1VZFcEZ/PdJkn1hOs8SXS/NFFgqt94PIZzZ3tdaL6Q5vo6piSzdy737pwsX1VyxUrF15iJ4uNkq+rbyg1Z+O8VsNC1UmcvORPRfxtPrfRwL2p/oA1eZp6Z/aGffoewaXcA/xBlKlQLfhQL/oPgBGP3qsA7IQS8qDVNswHKRSheDUvA3Q7MZoRcJMxlEygujn1QdyzfPfq3dEp/bXh5e5YXW2Ngfvza0ZF6UgFL/E0fTq4LBlvTE2qb/KuuzYSXVnjTfM1osvqMHVbm9950quIZlbqaL6YP7jk3kUtA0GnX2nvq53f3WoSsvEdDRnULgo2fN7lNZJgI8/VWi33c3bBZnGY05+dm+3qc7fNmj4YGKLj2nfqFP+g7jdDlxEV5XsJQZP6hYrS1l0VQr4c69Xueixp90gnZPmE5OF22j+SYEWHlZ0K/Hgsh/Ztsbh6h2DNRlvv6jJh9XaJaHCZDiUDKNTMkvb8vsqCyf3ZNdSmO0fa0Y4baJTtpbKzuVzeeSI7fCKr2Z0WypapnXJ4gnoWy3PoUIlIQ1TXdqhQJIXp9Wx5fYdpeWh2TY5D+YVyKd0jw3iumwi/BC3cEy4o83QlZnW79MrCgCjbhWXBlRZVVZZv4rIKpXC01HFlHdHLoeWVl6UVc/J5uGm6CViW5mulYMk+HqNYr0AyUPivLg2oMs2MPqtuhHyRyiwvNJej1Br+fcLyoAyu8D9B7bgmzUqfFobF5nKnK4+t8MPJkI/xHUNWk117jugWF+xazTAALQn6+UE9lhoI5ApGA/iuJOsrlNP28SVVuBVajXmircLel46w2bJS1Q0Ft0KDuikDFL/3pYrid1Q4FvofwRIo4R9h2ftSwc6jHAMqLcCql8YPHtlzGoByNXYN6v8hXnRaOhUvx0sVLCexwupGDR4NOYC7PePa5keIPACnuAdD7dEadRuTIiS6Lb7uskb381My5yjzF8lGCjBRqdwrWJCagfB3yCy7XT1i92hbcZ5Ci1FJkgYMDf6n+jspIsHFjJrTOdzSMuOa9DbDcj/nH9N9bIoGVgzHPWIQuFuYtaMRaq8eCKI0gEF6lPOZjBz3EEvaaxwSUT9U/8JbJZPJJLBLolH1La/RbF9AbC8JJjv/mMnssKjLRBJyqj9QXxNko0Ux/X79epfiXkm6fmKwF/en1HLc6LxloXWKvGa5rVCVL83VuiPcDEX/K5pTXOxHfx6HHB0t2FI0qI2rCZFTrvPWU67zVuS/kTsLnc7IKhFg30e4FOkqNSfH5PtkmUy6Cpiv/36k2sbqCeCFNa+URpoY0sZoYmCgCr3qgZz6s8I0gP1bYiR+D79H56NOz0EVWCTy2/fffvSCCx59W7uRV9995eqrX8GLesOXNm360iZ+T/El3uZqL+FyzSZ8XxpTiI/G0nkT4zznFZ0t4ipMz5v4q9ssqbdKUZt6u82knPCrt6PZwsnn0XySVnyPR1ZXAn72yx48bWJsu7apnI3Hy8bygUK5Js32qcytapqgmn95uexccj205vGgJ+euOeG2SORmKZr/qKzcx9SFctMJdwMUFZDJITs7dnOp1EKZCxg304Cevyfya+vlKqv6aXK1qIj3imL+L6hL+yvUlFfE0VKZ7E8gBY3M/8VoJCFgizH1W6VyC76nH6b7jiibYVxUmVIEspry/LgZIlCeP11Z4zs/AwvVwtGFEut5S1JY4lfyT0N/evOLo+rUEgjcqc9IkGpQbv3iW7Co5b+KgjvpzYdH85PLcc4X21ouwEGl/S4qnUAvoSlXUUhR1eKr2VWFTB+GMl6FsiQsVD1R3urlAAIoSn7JQkmiVVCHSpCwDH/qPepXQ0Db77CJOAImohB+RPWr31ev5g/kE+zTa4lbvZo8xdWPffQu9yJTPCNB66s+zXoJt/0L6hSoCuBIoK8fnBGG87OoRckJpLqyWe4YbpGi50g0+3I3UD85Oa0fzubfoXxPLbW3FDWzigmyJeM0tQkax7PqTy80+UxfUHPlBZIRVNQ+v0xRm8REKPoLmNr0+Uo48v9GFbXPKylqQ2IKm00QddgyWGMROCTxdLB9nCY8P7j2DjlsV/+mfr0C0r/NkeXbbpPlOTBBwT0mVz1zx9S/wJecBF9Wgv3p032iP2v4VSgfgW2G+HUEdEXU6iq4CtpLJfIN9XQG8dwa1VoO8XC2SrPDDyCOQptXgbcPvlAgBfxBoGwftQKeKFrNTASPt3pGGqDt/QRasn2kri+H6L80MJRsmVYJrAKyDItpJUy3/15WYIJqcJ9Q5N/LFJ4c3dc1URpWl9hW6mu50MUIelg4ucTPf15zs5DFo1c0VSp1tKB9jkwIyuM45kb+IP8gHed+6jO3v0KbIknzLy636E8KPTdCuUpB0wLo9JKnAO6pv0vS31EtBha/fJemkgLVVnd8KCk4qBTpQ5m7FbifBKrPJcq0pZAFVG/XbOFz+Tcq2MLrcmV28Nmi/OHskh82bau0k8eWCaPijQPWQ5lUvslwVCfHkXBMIehqUgtDNLeauH1huvZTbYmw+luPjyWoNGEuxRLR7LK5fSyXFUyK7PURQv2v8D3XOt2NJ6liBbmPGOsakw1kbeOs+31Wm5qpH+iJWSzqdPr2O7zc2TmtnrzCig6bBd/vgQmzOlz0STWIlmZEQfupogOZFHUZ7EkUnMn0RrpIMqAgHRJAOjIJ3yGw1I/MAp9q9S3Q/clADNm1wEeO+xbwg5OIYHZLY3ehG5lJk2xhco+6JWybpEVz2wrR6hZyD0QXZbeDVB+onmlimpkWprdAs4WEZDSQppsDlcdCBJJESIYFuAtUnC4GIF2C3Uu2Kv7L1bdz6FxtqxpG4TqQOqOUNAJ2HLvPWA2GgDy4O4vaDrtyl6P+1fAll+SyFcQ28GHqh7fvvf37udylf0fNwhzgz87Y+cf5x9GnF6ygHu18sAbipWeF0YPBgp2GaKeQduxxdEr3SgbH1kvH7tvqSLhedomOvZyts2dw8acu3dY/f+ucuMtCuP/e4zC4XnH3OLZ8ZuxTWxy8dJfU5dhDeKPSlJy5pn/+7u3XrJhmr9C5CuleGflGQocKnlAUaRKp0BAHV0ZwUt9VCqk6zYOgRIuMfePJzdmBdpPJ7/6B23+f+sp9NMDZevovvfYHG5dGPISQq1DojqNckchVrCcCYz/Q0hI0m3NKDRfkgsrnamo+p0CAq1FyvC3a3Nak/s5VX282x9Ufy3E39VAx6o7LpCvO2wK+ch9jNqpJCutcIOooKnYWtDK8gTRVYygRQfwgzKM5+jP2jOZdx3r32Py7rQUPOzAnoRs95NvRAR0qLGU11Taqu1bUYSzMcWjMEir067JQQHfIrLBHsrgv00/Wavd8HRLMEEYFSW3HCSNQehnrHztKqHcDyo4VfZ6gPKCR+gufwA8GegxUEo4A+gd0BASHiH6jYMLIsUdQJTs/C641KN4oCHWolCMLlMfIdtWKScjx7SM5LD9HnfmhrGI0S139UWfUnxgOXdJFW+AMcGjKr6eHAttHF5sUoeArYKDcxMSYcKA/xUDhPiEOEAPafSIUFArN0r24ynI91EPARDXvIDYyvqZaWeroBOUABQA/E+DXC7PWafDLQY2oiwpUEyj4RQtVlUp1GrM7In2p2A7VuiOW6otMiGOo5Mrp05ejVuTy6dNX/k/7mybZQ0nUmfrbx3U4KueDnlHm5wdh8FFeKnoaKKh/TK18StOPhwG9Xo5mqXAxvw/79YQwwDR+nAKQQ4izVXioB84qcppWB7IqjU45z4CE17OvF1Dw+oTFqxtz8dxwtogBnF9MjIl/in+K8s3hM9laIn0TiCbTAXL0T798bPXqx36p3chrv0O+GC9Xaj48Ecv8U8UEeBvUEsDlTepiU5OvlpeNGvpnKF0RvUooWhIjnx6GeBapXCQYTw9DNg6/OC3gZjp76oNTj9Kz6Jqobxb9NDqc08vcKReOpcsQV2K8InXFaXW3aI6Ofr1k48rp7CX7rx+v1UKPsfvzQU0Kc83i2VdILmd2/yX55zT9luN2+Cu4nKfwPcK/CvDVU+pHh8+LaldIf1fA5h3ndT6Fln9/W/9Ce1vndfvJtnPVO2xhm3qbafHVCN1X363UXHq9xuVD8OSD29Z8pZ5cZrern9cAdGW/uib/ud+VK0L9a42r6C90kL8KzxwLQw9NkIQJL0ASU8M+VG0KsUdgdvpgP/6NqqP0/gHZFUfGEijZLHpiIgvV5/Bltrj8Qd7XQd5p4P+7tJo30NMO6VGBwahSPMYiaaBYoLY6uEnciyhhh1Z/vvacG/rjpsvnpzs0B1Id6fmX8119l88XnOxe/uGrzzHcdu7UtY3+2vmXN5zUyj3ZcPl8p1sZSs6/nGXtwrV7Ka0XZdz83fwjjINpZWYw85lL8BRK4nGyIir2RiOsEyipuEcIakpGjWgBjLiHWOgj0Yi34gW1kKPxHt2Na5q+lwg1RdRSpFDNzosb44YJXnAfoEOpZW//6u1lhYA6leevezbI26zNHO811M2dc5HFxpk4i1jPC0s21/BWW5DnPQbn2X1WK43/aM2n18DfSoybbNHijFpamzXI31eRibGUOxSu/lT96YZlq1Yt20DaSBuG6knw2eusHs5EPBfNmVvHKdaQzcDfz9ZsXmLDWGXy2U5OsYSsIn8CS12jQIyD12KKqZrLPy7mSPdICmd6WGHG8NDZkkHuE4h9TU8FpmUO/VjC/EinToFyoNDz2p9XD6g78WgQdPG7Z3R0T/Z5dTM9lsL8Ktek7szl2L+gQwGgwkZHc2g5Su7NvVqwGy2Ua4KSXUwt1X4PaM5paaEu6jQ5zVFyNabxvUksVt2T/4VeamYPlLtffdQsk+2sUTY/zDXl/05W53/Bz9UK3p7LjapZ2ZxOm+UlZXrL3HHGqO8+wVroDaCTTnTxitMxmiAAYQzVJQH+nj3oIHnPaN6Zq6sNSLjBl8tKgVr2mj/9CWi9dnKca8rBQBsd5R1tzVlgrl5pbnPw6kZclCr2CHxMnHohLz+3KRQokzALyeIKFU1TNCiayJdoHvDYe7K6mZLm8S3uJ9dojuaJ62/qN/tjQxnSnhnKPw+LNrLi8ZKyJ3x1YhiI1aNAtP6NzCGzYv3DmaGh/LvQZnt0evgIhTFV0kE/PYxAnOHhCQUZdCWY5JWJwMzlAGl1mpNbDU7yyGnhRMILsYhH3VRAijrPcBU8/Cj1Y9NY6cnGVW0CjTLaz7E3epvaT/LtTV72Rs+0WVVmd0dz/MGTI5F0OsIviaqDlbbO5X6xT3PeXbXHRtf/z+fdka+eKPr8KF7IF4vBsT9MFPuPJMBTBMq9hQxXelQ+bewnf18ap4Ib+mSMrtDU5zqlD8QANa5MBGh/OwOvSDfcV2d66mfEWsbGWmIz6nsyZDWQSmqmxDneYyvjHPmRXHZxeueyRGLZzvRioKnGto9nIPkibAJA16adcOZRQr1iAP3bUyBR7T4RgAWTKxhkCYFwshq+7iV9r0whk50cmRcTg4fy5x4OmmNkHndIA2+YuMbmE9dwGYB4KFTsvnDE6Ah47r/fE3AYI+oXADpkdlENcZ8OZEEf8FFGZNxMs6ZLpG3SUFLL7Q2kcFU/A/Jsw+vWDa/7emewLaoeibaF1B9qUNnuqWK3+UfXYVL1v/omD15xxeDkPnXTOKSVcCbDGtOu0YQNpGAP7U1HU58UrqGu8xIbHtkQ3LVhb7Dx46ET3Ffcm1q0YcOizNmf3bC3VjWfAcpSv3MyTlgJ23FHQgmgvk+gk8pL0mcCDOn08MDAQlf+/SlTZ1z12fnqntOhbOTL9/ZdevbAPN+yby1f/uUtC/ixm8ZBo59LTXEW060hGrTDplNprWd58fwB/b/E27BdS/s7U+rGVCeQ46nzaw9QccnmZerGZZs3Yw9aVHt+Kh6HN4ti6lxIhT/wahnZtWwzlY9QHQ2c79C+dxzvVDKy8GqKWQERO9YAKbpsDUTLdWV5dE8PVPjvj9pqw7ah/PFVtkit7aj6G5xY9mfJrCz1j1e0BcnPol4UjtrCdbahIVtd2HaURujnFJR8CuOuUUfhrGhgKKgjCYNSvCc1WKlEp8wHUaAYynFNyzZn+2MnYv36dbMDBTonl/T/ma5IKAyEGz+4eRnVtaX6tss2o34u8mWorFtuFgm4A6qK/yp/gLEBVat5WnPDdKA574ubuFJ/IUfZ/Y2Nt6mN+ZNNTSTaeI56gKwkXerTe9DDHUw8/H35FY3nNN7GGuBKWhrV9ep+0k1WjNWVaHkW1yA+QHWNu8rtBw2a5YXuE40rs7/GA+j09V3hA98yRnFPOGr8ltGlsFdD/7tRce3LH6Trcneuiy7K7J3khKu+3qUaXPWaX7T6/Kfj9BX2eZq2XAcZT79u1ClJzUtHUqfqSMWBcZS43Ena0cUGLgpkKxB1QM+0Fxz10wgg6r5rltnFpH05pepUq3Y2HfYqeKRntmUFNz+XmcOs1H31U6cC6RTVLfCg7RNBF1UF2/wBgu0fFQtPEU1sSg3VcNsR7dWq3af87tUFn1l3ltXpaJxpNvtcZkH2WmMst3JqRpxUH+WC0E1qOGtP66s1MYv+VLu8/XFXvV/ZbunYYBeVN64ls0ur6NzpV9xzlmQwB5qC4Tq70WC0tk8dWJXeHvkD0h9zJOM0vD86/1NJMaIAolctvlByferCsqOKDKceOfUu1PsmoFCamV5mCrMUOCi6V6FJosMF22AcrKJgQDVhfYh6tepp/lYgvnCEAbJQ1L0rOpajEmRcasMiPfxhgGoVo4rwreQpV6fUJHH2e8fa1s2c13Apl1b89a58ozdoap2sjgLN9uISl7P1DrulyeIkt0zr6JjWocoPOZsaXPb6jtqBblsgsaRre2xHi4nELm0MhG1+x1SXwLpFi53b+aHRYo/IrbZtuWAKu5cSEXfybnnmUCaXGTpQr0xK2O2WWY76f+nAjNVf7nCZHU5XqIkTnpt6VtvsFlPXg1031g/VRdpkkyVpD7jnmax88QwDvg/66NnMRdRXTcGTmQc3cuINwN5IQqi0yzb+YFVHuVqI5s4ADfg5oE4ybDLd28mFSFmYvRoomsWXEdLU2Wl3GJy93ZNb/d5gqmNaqJZSO1l6PVRy0nZIj/45EetjLguh1rLqR+SK0hO6NrsqcNX8zoUdjQYDJ7tb4os6+i+Y0qpY2AWlnLRDWdGFTfGY1gV0zNAtJ7pdo24se0D88AwLY/gZmE9iuP4V5v7CSR/RThaHLh+UeBkXwU6BC7lGOevK65udTv+tS/PfW7qj3ljTcj3b9OkbV85t8xsMj7Ddj7DGpthZKwKPvso/c/1K9aLE12fMWLV1y1D9ua8lyJdWXr/bG+noCFutf/mLILe39ITUV4igr3876fpX5g2zeB52sWnIL4fXHlgeUzOx5QfIvJQyrKQE9wHUqVq+PEaOrz0wVvNbJZVSfsuMzxN4l9PkedFzw9V5Dj+nzpgoT4ZxCxJfC5RWLc74YVHxKlExCYt0JAOMatREhHBSCAtSfod6x6Ls8HCWECLwXZ9nd5Dz1T24JUdWs6fU3++fcnT49Qe+kBs+wdsMZgPXMp3U5S958snPP/EE7bvkOPCuTUDTUQ/UzirLhML9yPahoe1D5Fj5jWsaoveyP00PehdUAHk/seDVWsvDWXXXsyn/4wfpXc2V3/Qxli3jl/5hj/83avSCfpTNxOEKLmTjxOEKuxgNlsQn0xgct724mhynupNW1Ph6o3RYS3/+2TJrzLlkFz+ip3qCHKf6eqW02QJLjBYuuj4sobhCWqa/YHGEHpcnumuWSOhxeaL7sOakNR6vvmo+YcfFA8UFXEPZf9UjyudIOyNwx/i90DdsujS/FX2UAwvWSVK4NxaMhAGw3oowp/uc8CTi7D2rBgZWwb/60faR7SPsEbjkXy4G0XaqhXPwe2cePjxjxuHD6ssQuR1fq6PF0E+o2t1nePTn8TUmxz/A3crMoCc7egESuoTHYc7mYdg6etORoOhR7BBGD+qJopELrl4S6cJNRtEAsLP/OdvnJq0Wo0GolY2Et9VFB2Kf+4bZvVyxfOMz3WdFfSIryj6DwWghre7aQbdiDrkTL3A3vNDuDpk93HqXwam+bWmUJZfNn5ozKV5Pmmq8PF/jVY+2Tlk2M2RzSXKjmbQ4RZcQavEYrN/9rlXwtIQqzxQNMzPPfHYLvuPoO9TbT8bpGw5CQPGd+SyX/Cyf0Vxjd2R9NmsunnXYa8xGHzn+sSfM5J0y0DZEXWWxkXjcR75KBLNLHi7XvX2G8VOrf4Ykg0AMdBESIpo7MgAfyakA6rkqpI6UjNs0px7cMV+D5BF49Tez1VGnYmq0WIijp985m4Sn2gJR9b07riPPFo97OYbUZbxJCpot7H/lpZBicglCPN7WOfJkcHqc3ElWqvvz/1E6bIQrG+tz6WkM1SM9FBTR7FSs8KyBBytSmNEoquJNFN5EQyTiCrnKDx1h58yxCepPHU5nxGoxEQeeOZi2m80DxNxncVhr6BmEfUarxejw+WSiHhWk19bSY7aKR5MsteblJpfTLtjimBouXsm3d3djjYM+wEW0El9dM/ueVRWIsXwe43R7SgbVZqrnqoJ1X/kuF7pcgf8duv4q6vayV5U9zMV91GxO59UUjW8rHV6u799WzKMT7umRCXbYUKM+foaCcwgaoqZUtmodV3p+X7akb4dnU9B9La38RPFUG2SCC90tVA4XwEFhyOpZZrUCsgWYHsczLFBBVGNtstoN1bw0Z+O4fYIbvZVt4EUcJEKOhHeincWqONw+q6w5Go+WGOSR7LhKV+KBqbBPpfUvOf9QqkpDyVhBeyyZQGMsdA5FBUqvFMtUyGq9vjnsAJU4UcrxldP1CCaofyDkSAifoP5QwWx+SyUGxp75BzGAvtG7uQ38LehlyEQMeh0TeE6Bm7tYdXqdkt0uOb3kfYlNwmOdDyacOq/qlFo1v+PTmTi3E/glC9W11b34A22zmLzvb231Q0L2Bgg60OTW4YdstO+YOJnO38TtpH7zy9ymokWyA79qlVSn38HtpFlImFnhu3b4boNWXklOXV0Iwo7lQ1hrZyPFcwtjwFP7iEKSHSSJw509kh8kj6pr+H1jR7km9vcvqN9657vffefkv+fKxge1X+7RdjYUPIESN7gTvRkB/RMYtEkaVkdHApmdBPpnKmz0n1xSWFOyVIuLrinZwpoCRe6kyiVZoHX088F+UX4+WKS4iBTP0IWxGtZgOdMaV4KTayqHQF/VihBwTbgDXTCmKoOBJeNhwJMzEVjtjIFLuU38fPR7hqNG1JS7g/qRCuy3vmQ3W9Vu8qbVbP+SzazGRJH83MzP90Ck2m31mMjP8TiLn5uwD2Ugr2PFvPQjB5BnSJvQxGQZZEB+LopqzGzDbMmbkAPkZVJjeO5FzOSBKCgJze2ZS4Gemc9twrwY6u9H61iUQTcRvtdT9RW3tRxAWwFs2tcuJRnI6xjmBdWjbgFNRHMHiF1uHYBfUR/ut5Ug2jXAaT96+9RH/FToRwIzGbKmVJ1AZQnoabSB1yyIg7ByAridHApPMjyw0OiV6RjSbCuzwLAvFizBliWJua1tsuAgvNPbmljYbpt8lkWam7b3XZiOiKJskMOtmfScnsbPW208knwjuXrXK4Q1iKIgNyYXXDVT9C2Ye/78GQ5BEEXfFdde2RwauOysdJNL5AzCy84ard/nGAVN8alecnFdgu5Gbd5DJTL+hHZK0vApVy3OfU8XTSJg1TlssivsPYUlIqvn66PzrVTymCc4wgF6SDNR0pDf+9Gp+VnsUH5WtpHYsuhOaey8zdwLN47V8MTbm78g687+P3cx6tcAeNpjYGRgYGBk8s0/zBIfz2/zlUGeZQNQhOFCWfF0GP0/8P8c1jusIkAuBwMTSBQAYwQM6HjaY2BkYGAV+d8KJgP/XWG9wwAUQQGLAYqPBl942n1TvUoDQRCe1VM8kWARjNrZGIurBAsRBIuA2vkAFsJiKTYW4guIjT5ARMgTxCLoA1hcb5OgDyGHrY7f7M65e8fpLF++2W/nZ2eTmGfaIJi5I0qGDlZZcD51QzTTJirZPAI9JIwVA+wT8L5nOdMaV0AuMJ+icRHq8of6LSD18fzq8ds7xjpwBnQiSI9V5QVl6NwPvgM15NXn/AtWZyj3W0HjEXitOc/dIdbetPdFTZ+P6t+X7xU0/k6GJtOe1/B3arN0/pmz1J4UZc+D6ExwjD7vioeGd5HvhvU+R+DZcGZ6YBPNfAi0G97iBPwFXqph2cW8+D7kjMfwtinHb6kLb6Wygk3cZytSEoptGrlScdHtLPeri1JKueACMZfU1ViJG1Sq5E43dIt7SZZFl1zuRhb/GOs44xFVDbrJzB5tYs35OmaXTrEmkv0DajnMWQB42mNgYNCCwk0MLxheMPrhgUuY2JiUmOqY2pjWMD1hdmPOY+5hPsLCwWLEksSyiOUOawzrLrYiti/sCuxJ7Kc45DiSOPZxmnG2cG7jvMelweXDNYXrEbcBdxf3KR4OngheLd443g18fHwZfFv4NfiX8T8TEBIIEZggsEpQS7BMcJsQl5CFUI3QAWEp4RLhCyJaIldEbURXiJ4RYxEzE0sQ2yD2TzxIfJkEk4SeRJbENIkNEg8k/klqSGZITpE8InlL8p2UmVSG1A6pb9Jx0ltkjGSmyDySlZF1kc2RnSK7R/aZnJ5cmdwB+ST5SwpuCvsUjRTLFHcoOShNU9qhzKespGyhXKV8SPmBCpOKgUqcyjSVR6omqgmqe9RE1OrUnqkHqO9R/6FholGgsUZzgeYZLTUtL60WbS7tKh0OnQydXTpvdGV0O3S/6Gnopekt0ruhz6fvpl+nv0n/h4GdQYvBJUMhwwTDdYYvjFSM4oxmGd0zVjK2M84w3mYiYZJgssLkkqmO6TzTF2Z2ZjVmd8ylzP3MJ5lfsRCwcLJoszhhyWXpZdlhecZKxirHapbVPesF1ndsJGwCbBbZ/LA1sn1jZ2XXY3fFXsM+z36V/S8HD4cGh2OOTI51ThJOK5zeOUs4OzmXOS9wPuUi4JLgss7lm2uU6zY3NrcSty1u39zN3Mvct7l/8xDzMPLw88jyaPM44ynkaeEZ59niucqLyUvPKwgAn3OqOQAAAQAAARcApwARAAAAAAACAAAAAQABAAAAQAAuAAAAAHjarZK9TgJBEMf/d6CRaAyRhMLqCgsbL4ciglTGRPEjSiSKlnLycXJ86CEniU/hM9jYWPgIFkYfwd6nsDD+d1mBIIUx3mZnfzs3MzszuwDCeIYG8UUwQxmAFgxxPeeuyxrmcaNYxzTuFAewi0fFQSTxqXgM11pC8TgS2oPiCUS1d8Uh8ofiSczpYcVT5LjiCPlY8Qui+ncOr7D02y6/BTCrP/m+b5bdTrPi2I26Z9qNGtbRQBMdXMJBGRW0YOCecxEWYoiTCvxrYBunqHPdoX2bLOyrMKlZg8thDETw5K7Itci1TXlGy0124QRZZLDFU/exhxztMozlosTpMH6ZPge0L+OKGnFKjJ4WRwppHPL0PP3SI2P9jLQwFOu3GRhDfkeyDo//G7IHgzllZQxLdquvrdCyBVvat3seJlYo06gxapUxhU2JWnFygR03sSxnEkvcpf5Y5eibGq315TDp7fKWm8zbUVl71Aqq/ZtNnlkWmLnQtno9ycvXYbA6W2pF3aKfCayyC0Ja7Fr/PW70/HO4YM0OKxFvzf0C1MyPjwAAeNpt1VWUU2cYRuHsgxenQt1d8/3JOUnqAyR1d/cCLQVKO22pu7tQd3d3d3d3d3cXmGzumrWy3pWLs/NdPDMpZaWu1783l1Lpf14MnfzO6FbqVupfGkD30iR60JNe9KYP09CXfvRnAAMZxG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padding-right: 8px;
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margin-bottom: 10px;
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margin: 0;
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.pagedtable th {
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border: none;
border-bottom: 2px solid #dddddd;
min-width: 45px;
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.pagedtable td {
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.pagedtable .even {
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.pagedtable a {
-webkit-touch-callout: none;
-webkit-user-select: none;
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cursor: pointer;
padding: 0 5px 0 5px;
float: right;
border: 0;
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color: #999;
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a.pagedtable-index-nav-disabled:hover {
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a.pagedtable-index-current:hover {
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border: 0;
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color: #333;
font-size: 9px;
padding: 0 0 0 0;
cursor: default;
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color: #333;
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padding-bottom: 5px;
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color: #999;
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text-overflow: ellipsis;
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text-overflow: ellipsis;
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font-weight: 400;
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        max: positiveIntOrNull(columns.max),
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      character: 8,
      height: 15,
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        end: end,
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      };
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      return rowStart;
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        }

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          // width in characters
          chars: maxChars,
          // width for the inner html columns
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        };
      });
    };

    me.getWidth = function() {
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      widthOuter = widthOuter + me.padding * paddingColChars * measurer.measures.character;

      if (me.hasMoreLeftColumns()) {
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      if (me.hasMoreRightColumns()) {
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    me.setVisibleColumns = function(columnNumber, newVisibleColumns, paddingCount) {
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      me.padding = paddingCount;

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    me.incColumnNumber = function(increment) {
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    me.setColumnNumber = function(newNumber) {
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  var measurer = new Measurer(data, options);
  var columns = new Columns(data, source.columns, options);

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  var header = null;
  var footer = null;
  var tbody = null;

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      "border-bottom: " + columnNavigationWidthPX + "px solid transparent;" +
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    var header = document.createElement("th");
    header.appendChild(arrow);
    header.setAttribute("style",
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      "width: " + columnNavigationWidthPX + "px;");

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      header.appendChild(renderColumnNavigation(columns.visible, false));

    if (typeof(clear) == "undefined" || clear) clearHeader();
    var thead = pagedTable.querySelectorAll("thead")[0];
    thead.appendChild(fragment);
  };

  me.animateColumns = function(backwards) {
    var thead = pagedTable.querySelectorAll("thead")[0];

    var headerOld = thead.querySelectorAll("tr")[0];
    var tbodyOld = table.querySelectorAll("tbody")[0];

    me.fitColumns(backwards);

    renderHeader(false);

    header.style.opacity = "0";
    header.style.transform = backwards ? "translateX(-30px)" : "translateX(30px)";
    header.style.transition = "transform 200ms linear, opacity 200ms";
    header.style.transitionDelay = "0";

    renderBody(false);

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      headerOld.style.transform = "translateX(0px)";
      headerOld.style.opacity = "1";
      headerOld.style.transition = "transform 100ms linear, opacity 100ms";
      headerOld.setAttribute("class", "pagedtable-remove-head");
      if (headerOld.style.transitionEnd) {
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          var headerOldByClass = thead.querySelector(".pagedtable-remove-head");
          if (headerOldByClass) thead.removeChild(headerOldByClass);
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      else {
        thead.removeChild(headerOld);
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    if (tbodyOld) table.removeChild(tbodyOld);

    tbody.style.opacity = "0";
    tbody.style.transition = "transform 200ms linear, opacity 200ms";
    tbody.style.transitionDelay = "0ms";

    // force relayout
    window.getComputedStyle(header).opacity;
    window.getComputedStyle(tbody).opacity;

    if (headerOld) {
      headerOld.style.transform = backwards ? "translateX(20px)" : "translateX(-30px)";
      headerOld.style.opacity = "0";
    }

    header.style.transform = "translateX(0px)";
    header.style.opacity = "1";

    tbody.style.opacity = "1";
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  me.onChange = function(callback) {
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    var pageData = data.slice(page.getRowStart(), page.getRowEnd());

    pageData.forEach(function(dataRow, idxRow) {
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        if (dataCell === "NA") htmlCell.setAttribute("class", "pagedtable-na-cell");
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      for (var idx = 0; idx < columns.getPaddingCount(); idx++) {
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    for (var idxPadding = 0; idxPadding < page.getPaddingRows(); idxPadding++) {
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    var pageEnd = page.getRowEnd();
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      infoText = infoText + " | " + (columns.number + 1) + "-" +
        (Math.min(columns.number + columns.visible, columns.total)) +
        " of " + totalColumnsLabel + " columns";
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    return infoText;
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  var clearFooter = function() {
    footer = pagedTable.querySelectorAll("div.pagedtable-footer")[0];
    footer.innerHTML = "";

    return footer;
  };

  var createPageLink = function(idxPage) {
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    pageLinkClass = idxPage === page.number ? "pagedtable-index pagedtable-index-current" : "pagedtable-index";
    pageLink.setAttribute("class", pageLinkClass);
    pageLink.setAttribute("data-page-index", idxPage);
    pageLink.onclick = function() {
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      renderBody();
      renderFooter();

      triggerOnChange();
    };

    pageLink.appendChild(document.createTextNode(idxPage + 1));

    return pageLink;
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    var next = document.createElement("a");
    next.appendChild(document.createTextNode("Next"));
    next.onclick = function() {
      page.setPageNumber(page.number + 1);
      renderBody();
      renderFooter();

      triggerOnChange();
    };
    if (data.length > page.rows) footer.appendChild(next);

    var pageNumbers = document.createElement("div");
    pageNumbers.setAttribute("class", "pagedtable-indexes");

    var pageRange = page.getVisiblePageRange();

    if (pageRange.first) {
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      pageNumbers.appendChild(pageLink);

      var pageSeparator = document.createElement("div");
      pageSeparator.setAttribute("class", "pagedtable-index-separator-left");
      pageSeparator.appendChild(document.createTextNode("..."))
      pageNumbers.appendChild(pageSeparator);
    }

    for (var idxPage = pageRange.start; idxPage < pageRange.end; idxPage++) {
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      pageNumbers.appendChild(pageLink);
    }

    if (pageRange.last) {
      var pageSeparator = document.createElement("div");
      pageSeparator.setAttribute("class", "pagedtable-index-separator-right");
      pageSeparator.appendChild(document.createTextNode("..."))
      pageNumbers.appendChild(pageSeparator);

      var pageLink = createPageLink(page.total - 1);
      pageNumbers.appendChild(pageLink);
    }

    if (data.length > page.rows) footer.appendChild(pageNumbers);

    var previous = document.createElement("a");
    previous.appendChild(document.createTextNode("Previous"));
    previous.onclick = function() {
      page.setPageNumber(page.number - 1);
      renderBody();
      renderFooter();

      triggerOnChange();
    };
    if (data.length > page.rows) footer.appendChild(previous);

    var infoLabel = document.createElement("div");
    infoLabel.setAttribute("class", "pagedtable-info");
    infoLabel.setAttribute("title", getLabelInfo());
    infoLabel.appendChild(document.createTextNode(getLabelInfo()));
    footer.appendChild(infoLabel);

    var enabledClass = "pagedtable-index-nav";
    var disabledClass = "pagedtable-index-nav pagedtable-index-nav-disabled";
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    measuresTable.style.position = "absolute";
    measuresTable.style.whiteSpace = "nowrap";
    measuresTable.style.height = "auto";
    measuresTable.style.width = "auto";

    var measuresRow = document.createElement("tr");
    measuresTable.appendChild(measuresRow);

    measuresCell = document.createElement("td");
    var sampleString = "ABCDEFGHIJ0123456789";
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    measuresRow.appendChild(measuresCell);

    tableDiv.appendChild(measuresTable);
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    var pagedTableClass = data.length > 0 ?
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    tableDiv.setAttribute("class", pagedTableClass);

    renderMeasures();
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    columns.calculateWidths(measurer.measures);

    table = document.createElement("table");
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    table.setAttribute("class", "table table-condensed");
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    table.appendChild(document.createElement("thead"));

    var footerDiv = document.createElement("div");
    footerDiv.setAttribute("class", "pagedtable-footer");
    tableDiv.appendChild(footerDiv);

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    me.render();

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    if (tableDiv.clientWidth <= 0) {
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  var registerWidths = function() {
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  var parsePadding = function(value) {
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  me.fixedHeight = function() {
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  me.fitRows = function() {
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      return;

    measurer.calculate(measuresCell);

    var rows = options.rows.min !== null ? options.rows.min : 0;
    var headerHeight = header !== null && header.offsetHeight > 0 ? header.offsetHeight : 0;
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    rows = options.rows.min !== null ? Math.max(options.rows.min, rows) : rows;

    page.setRows(rows);
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  // The goal of this function is to add as many columns as possible
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    var columnNumber = columns.number;
    var paddingCount = 0;

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    var columnHistory = [];

    var lastTableHeight = 0;
    var backwards = startBackwards;

    var tableDivStyle = window.getComputedStyle(tableDiv, null);
    var tableDivPadding = parsePadding(tableDivStyle.paddingLeft) +
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    var currentWidth = 0;

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        break;
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      columnHistory.push({
        columnNumber: columnNumber,
        visibleColumns: visibleColumns,
        paddingCount: paddingCount
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      if (columns.max !== null &&
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        break;
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        if (!startBackwards && columnNumber > 0) {
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          backwards = false;
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      // when moving backwards try fitting left columns first
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      if (columnNumber + visibleColumns < columns.total) {
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    var lastRenderableColumn = {
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        visibleColumns: visibleColumns,
        paddingCount: paddingCount
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    if (columnHistory.length > 0) {
      lastRenderableColumn = columnHistory[columnHistory.length - 1];
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    columns.setVisibleColumns(
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    if (pagedTable.offsetWidth > 0) {
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    registerWidths();
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  me.fit = function(startBackwards) {
    me.fitRows();
    me.fitColumns(startBackwards);
  }

  me.render = function() {
    me.fitColumns(false);

    // render header/footer to measure height accurately
    renderHeader();
    renderFooter();

    me.fitRows();
    renderBody();

    // re-render footer to match new rows
    renderFooter();
  }

  var resizeLastWidth = -1;
  var resizeLastHeight = -1;
  var resizeNewWidth = -1;
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  me.resize = function(newWidth, newHeight) {

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      if (
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        resizeLastHeight = resizeNewHeight;

        setTimeout(resizeDelayed, 200);
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        resizeLastWidth = -1;
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    resizeNewWidth = newWidth;
    resizeNewHeight = newHeight;

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};

var PagedTableDoc;
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  window.addEventListener("resize", PagedTableDoc.resizeAll);

  return PagedTableDoc;
})(PagedTableDoc || (PagedTableDoc = {}));

window.onload = function() {
  PagedTableDoc.initAll();
};
</script>
<script>

/**
 * jQuery Plugin: Sticky Tabs
 *
 * @author Aidan Lister <aidan@php.net>
 * adapted by Ruben Arslan to activate parent tabs too
 * http://www.aidanlister.com/2014/03/persisting-the-tab-state-in-bootstrap/
 */
(function($) {
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window.buildTabsets = function(tocID) {

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};

</script>
<script>
window.initializeCodeFolding = function(show) {

  // handlers for show-all and hide all
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    $(this).before(div);
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}
</script>
<script>
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<h1 class="title toc-ignore">Negativity Biases and Political Ideology: A Comparative Test Across 17 Countries, Replication File</h1>

</div>


<!-- rnb-text-begin -->
<p>The file that follows replicates all analyses in Patrick Fournier, Stuart Soroka and Lilach Nir (2020), Negativity Biases and Political Ideology: A Comparative Test Across 17 Countries, forthcoming in the American Political Science Review. Analyses were done primiarly in STATA, with selected analyses for figures - and the figures themselves - drawn in R. For this reason, we are distributing this RMarkdown file that pulls together all the various datasets and analyses.</p>
<p>The only graphic that is not produced using the distributed script is Figure 5, which offers descriptives for the IAPS pictures used in the study. Those descriptives must be downloaded here: <a href="https://csea.phhp.ufl.edu" class="uri">https://csea.phhp.ufl.edu</a>.</p>
<p>There are five different datasets distributed with this RMarkdown file:</p>
<p>Sample-description.dta &lt;- The respondent-level dataset including all responses, not just those with working physiological measures.</p>
<p>Individual-data.dta &lt;- The working respondent-level dataset.</p>
<p>Stimulus-data.dta &lt;- The respondent-stimulus-level panel dataset.</p>
<p>Time-series-data-photos.dta &lt;- The times-series by-respondent panel dataset.</p>
<p>Time-series-data-videos.dta &lt;- The times-series by-respondent panel dataset.</p>
<p>Analysis run in STATA are stored in STATA do-files with names that correspond to each of these datasets. Those STATA do-files can be run in STATA, independent of this script. Alternatively, the current file produces the figures alongside reading in and processing all of the STATA do-files using the RStata package.</p>
<div id="setup" class="section level2">
<h2>Setup</h2>
<!-- rnb-text-end -->
<!-- rnb-chunk-begin -->
<!-- rnb-source-begin eyJkYXRhIjoiYGBgclxuXG5ybShsaXN0PWxzKCkpXG5cbmxpYnJhcnkocmlvKSA7IGxpYnJhcnkocGxtKSA7IGxpYnJhcnkoUlN0YXRhKSA7IGxpYnJhcnkoZWZmZWN0cykgOyBsaWJyYXJ5KGtuaXRyKVxuYGBgIn0= -->
<pre class="r"><code>
rm(list=ls())

library(rio) ; library(plm) ; library(RStata) ; library(effects) ; library(knitr)</code></pre>
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<pre><code>Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
The following rio suggested packages are not installed: ‘csvy’, ‘feather’, ‘fst’, ‘hexView’, ‘readODS’, ‘rmatio’
Use 'install_formats()' to install them
Loading required package: carData
lattice theme set by effectsTheme()
See ?effectsTheme for details.</code></pre>
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<pre class="r"><code>options(&quot;RStata.StataPath&quot; = '/Applications/Stata/StataMP.app/Contents/MacOS/stata-mp')
options(&quot;RStata.StataVersion&quot; = 15)

#setting countries
countries &lt;- c(&quot;BR&quot;,&quot;CA.e&quot;,&quot;CA.f&quot;,&quot;CH&quot;,&quot;CN&quot;,&quot;DK&quot;,&quot;FR&quot;,&quot;GH&quot;,&quot;IN&quot;,&quot;IS.j&quot;,&quot;IS.p&quot;,&quot;IT&quot;,&quot;JP&quot;,&quot;NZ&quot;,&quot;RU&quot;,&quot;SE&quot;,&quot;SW&quot;,&quot;UK&quot;,&quot;US&quot;)
ncountries &lt;- length(countries)
</code></pre>
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<pre class="r"><code>
S1 &lt;- import(&quot;Sample-description.dta&quot;) #respondent-level dataset
S1 &lt;- S1[S1$country2!=&quot;&quot;,]
S &lt;- import(&quot;Individual-data.dta&quot;) #respondent-level dataset
S &lt;- S[S$country2!=&quot;&quot;,]
R &lt;- import(&quot;Stimulus-data.dta&quot;) #respondent-level dataset
V &lt;- import(&quot;Time-series-data-videos.dta&quot;) #respondent-level dataset
P &lt;- import(&quot;Time-series-data-photos.dta&quot;) #respondent-level dataset
</code></pre>
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</div>
<div id="analysis-of-sample-description.dta" class="section level2">
<h2>Analysis of Sample-description.dta</h2>
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<pre class="r"><code>
TAB &lt;- as.data.frame(table(S1$respnum))
TAB&lt;- table(S1$female,S1$country2)
TAB &lt;- TAB[1:2,ncountries:1]
{
pdf(&quot;figure.1a.pdf&quot;, width = 4, height = 6, bg=&quot;white&quot;) 
barplot(TAB, las=1, legend.text = c(&quot;Female&quot;, &quot;Male&quot;),args.legend = list(x = &quot;right&quot;, bty = &quot;n&quot;), horiz=TRUE)
title(main=&quot;Respondent Sex&quot;)
title(xlab=&quot;Sample Size by Sex&quot;)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
{
pdf(&quot;figure.1b.pdf&quot;, width = 4, height = 6, bg=&quot;white&quot;) 
plot(c(18,70),c(0,ncountries),ylim=c(.5,ncountries), ann=F,axes=F,type=&quot;n&quot;)
title(main=&quot;Respondent Age&quot;)
for (i in 1:ncountries) {
  Q &lt;- quantile(S1$age[S1$country2==countries[i]],c(.25,.75),na.rm=T)
  arrows(Q[1],ncountries+1-i,Q[2],ncountries+1-i,code=3,length=.05,angle=90,col=&quot;gray&quot;)
}
for (i in 1:ncountries) {
  M &lt;- mean(S1$age[S1$country2==countries[i]],na.rm=T) ; points(M,ncountries+1-i,pch=15,cex=1.2)
}
axis(1)
axis(2,at=c(1:ncountries),labels=rev(countries),las=1)
title(xlab=&quot;Age, in Years&quot;)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
{
pdf(&quot;figure.1c.pdf&quot;, width = 4, height = 6, bg=&quot;white&quot;) 
plot(c(1,2,3,4,5,6,7),c(0,2,5,6,7,11,12),ylim=c(.5,ncountries), ann=F,axes=F,type=&quot;n&quot;)
title(main=&quot;English Proficiency&quot;)
for (i in 1:ncountries) {
  Q &lt;- quantile(S1$english_prof[S1$country2==countries[i]],c(.25,.75),na.rm=T)
  arrows(Q[1],ncountries+1-i,Q[2],ncountries+1-i,code=3,length=.05,angle=90,col=&quot;gray&quot;)
}
for (i in 1:ncountries) {
  M &lt;- mean(S1$english_prof[S1$country2==countries[i]]) ; points(M,ncountries+1-i,pch=15,cex=1.2)
}
axis(1)
axis(2,at=c(1:ncountries),labels=rev(countries),las=1)
title(xlab=&quot;English Proficiency&quot;)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
stata_src &lt;- readLines(&quot;Sample-description.do&quot;)
stata(stata_src,data.in=S1)</code></pre>
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<!-- rnb-output-begin {"data":". *** Syntax for descriptive statistics of the complete samples (before SCL pro\n> cessing)\n. *** Use data file 'Sample-description.dta' with this syntax\n. * Figure 1\n. bysort country2: tab female \n\n-------------------------------------------------------------------------------\n-> country2 = BR\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         19       44.19       44.19\n          1 |         24       55.81      100.00\n------------+-----------------------------------\n      Total |         43      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CA.e\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         23       41.07       41.07\n          1 |         33       58.93      100.00\n------------+-----------------------------------\n      Total |         56      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CA.f\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         24       66.67       66.67\n          1 |         12       33.33      100.00\n------------+-----------------------------------\n      Total |         36      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CH\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         18       46.15       46.15\n          1 |         21       53.85      100.00\n------------+-----------------------------------\n      Total |         39      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CN\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         31       48.44       48.44\n          1 |         33       51.56      100.00\n------------+-----------------------------------\n      Total |         64      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = DK\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         22       53.66       53.66\n          1 |         19       46.34      100.00\n------------+-----------------------------------\n      Total |         41      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = FR\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         30       46.15       46.15\n          1 |         35       53.85      100.00\n------------+-----------------------------------\n      Total |         65      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = GH\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         36       48.65       48.65\n          1 |         38       51.35      100.00\n------------+-----------------------------------\n      Total |         74      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IN\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         32       55.17       55.17\n          1 |         26       44.83      100.00\n------------+-----------------------------------\n      Total |         58      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IS.j\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         40       46.51       46.51\n          1 |         46       53.49      100.00\n------------+-----------------------------------\n      Total |         86      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IS.p\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         14       41.18       41.18\n          1 |         20       58.82      100.00\n------------+-----------------------------------\n      Total |         34      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IT\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         12       30.00       30.00\n          1 |         28       70.00      100.00\n------------+-----------------------------------\n      Total |         40      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = JP\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         21       48.84       48.84\n          1 |         22       51.16      100.00\n------------+-----------------------------------\n      Total |         43      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = NZ\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         20       50.00       50.00\n          1 |         20       50.00      100.00\n------------+-----------------------------------\n      Total |         40      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = RU\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         15       34.88       34.88\n          1 |         28       65.12      100.00\n------------+-----------------------------------\n      Total |         43      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = SE\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         36       62.07       62.07\n          1 |         22       37.93      100.00\n------------+-----------------------------------\n      Total |         58      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = SW\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         18       52.94       52.94\n          1 |         16       47.06      100.00\n------------+-----------------------------------\n      Total |         34      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = UK\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         23       34.85       34.85\n          1 |         43       65.15      100.00\n------------+-----------------------------------\n      Total |         66      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = US\n\n     female |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         81       34.32       34.32\n          1 |        155       65.68      100.00\n------------+-----------------------------------\n      Total |        236      100.00\n\n. bysort country2: sum age english_prof \n\n-------------------------------------------------------------------------------\n-> country2 = BR\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         43     27.4186    8.572471         18         55\nenglish_prof |         43    4.302326    2.087775          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = CA.e\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         56    23.01786    4.047406         18         40\nenglish_prof |         56    6.785714    .5296409          5          7\n\n-------------------------------------------------------------------------------\n-> country2 = CA.f\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         36    37.02778    14.13099         17         63\nenglish_prof |         36    6.111111    1.347543          2          7\n\n-------------------------------------------------------------------------------\n-> country2 = CH\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         39    37.58974    12.25973         20         66\nenglish_prof |         39    3.051282    2.139217          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = CN\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         64    25.92188    4.667703         19         39\nenglish_prof |         64    3.890625    1.481282          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = DK\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         41    35.21951    14.17835         21         64\nenglish_prof |         41    5.609756    1.180636          2          7\n\n-------------------------------------------------------------------------------\n-> country2 = FR\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         65    28.47692    11.28066         16         58\nenglish_prof |         65    5.353846    1.304209          2          7\n\n-------------------------------------------------------------------------------\n-> country2 = GH\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         73    31.41096    10.82799         18         71\nenglish_prof |         74    5.662162    1.407193          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = IN\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         58    33.84483    8.675033         22         61\nenglish_prof |         58    4.344828    2.164723          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = IS.j\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         86    24.18605    3.219469         17         35\nenglish_prof |         86    5.930233    1.281458          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = IS.p\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         34          19    2.059715         16         25\nenglish_prof |         34    5.205882    1.493002          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = IT\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         40      24.275    5.769004         20         57\nenglish_prof |         40       5.625    1.314368          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = JP\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         43     21.5814     2.01462         18         29\nenglish_prof |         43    3.674419    1.643471          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = NZ\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         39     47.5641    16.92677         21         66\nenglish_prof |         40         6.9    .3038218          6          7\n\n-------------------------------------------------------------------------------\n-> country2 = RU\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         43    32.46512    11.84493         20         61\nenglish_prof |         43     3.27907    2.003872          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = SE\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         58    31.32759    9.827259         18         63\nenglish_prof |         58    3.034483    1.815774          1          7\n\n-------------------------------------------------------------------------------\n-> country2 = SW\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         34    43.52941    13.71846         24         66\nenglish_prof |         34    5.676471    .9118941          4          7\n\n-------------------------------------------------------------------------------\n-> country2 = UK\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         66     40.0303    14.28821         19         74\nenglish_prof |         66     6.69697    .5809726          4          7\n\n-------------------------------------------------------------------------------\n-> country2 = US\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |        236    25.49576    12.91395         17         69\nenglish_prof |        236    6.915254    .3707674          3          7\n\n. * Table 1 Last Column\n. sum story11_rating3 story12_rating3 story13_rating3 story14_rating3 story15_r\n> ating3 story16_rating3 story17_rating3 story18_rating3\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\nstory11_ra~3 |        571    4.584939    1.785237          1          7\nstory12_ra~3 |        453    3.754967    1.686622          1          7\nstory13_ra~3 |        623     4.81862    1.974314          1          7\nstory14_ra~3 |        593    5.092749      1.8297          1          7\nstory15_ra~3 |        628    1.745223    1.133255          1          7\n-------------+---------------------------------------------------------\nstory16_ra~3 |        616    1.474026    .9470402          1          7\nstory17_ra~3 |        563    1.321492    .9626568          1          7\nstory18_ra~3 |        635    1.496063    1.009997          1          7\n"} -->
<pre><code>. *** Syntax for descriptive statistics of the complete samples (before SCL pro
&gt; cessing)
. *** Use data file 'Sample-description.dta' with this syntax
. * Figure 1
. bysort country2: tab female 

-------------------------------------------------------------------------------
-&gt; country2 = BR

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         19       44.19       44.19
          1 |         24       55.81      100.00
------------+-----------------------------------
      Total |         43      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CA.e

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         23       41.07       41.07
          1 |         33       58.93      100.00
------------+-----------------------------------
      Total |         56      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CA.f

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         24       66.67       66.67
          1 |         12       33.33      100.00
------------+-----------------------------------
      Total |         36      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CH

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         18       46.15       46.15
          1 |         21       53.85      100.00
------------+-----------------------------------
      Total |         39      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CN

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         31       48.44       48.44
          1 |         33       51.56      100.00
------------+-----------------------------------
      Total |         64      100.00

-------------------------------------------------------------------------------
-&gt; country2 = DK

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         22       53.66       53.66
          1 |         19       46.34      100.00
------------+-----------------------------------
      Total |         41      100.00

-------------------------------------------------------------------------------
-&gt; country2 = FR

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         30       46.15       46.15
          1 |         35       53.85      100.00
------------+-----------------------------------
      Total |         65      100.00

-------------------------------------------------------------------------------
-&gt; country2 = GH

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         36       48.65       48.65
          1 |         38       51.35      100.00
------------+-----------------------------------
      Total |         74      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IN

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         32       55.17       55.17
          1 |         26       44.83      100.00
------------+-----------------------------------
      Total |         58      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IS.j

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         40       46.51       46.51
          1 |         46       53.49      100.00
------------+-----------------------------------
      Total |         86      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IS.p

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         14       41.18       41.18
          1 |         20       58.82      100.00
------------+-----------------------------------
      Total |         34      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IT

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         12       30.00       30.00
          1 |         28       70.00      100.00
------------+-----------------------------------
      Total |         40      100.00

-------------------------------------------------------------------------------
-&gt; country2 = JP

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         21       48.84       48.84
          1 |         22       51.16      100.00
------------+-----------------------------------
      Total |         43      100.00

-------------------------------------------------------------------------------
-&gt; country2 = NZ

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         20       50.00       50.00
          1 |         20       50.00      100.00
------------+-----------------------------------
      Total |         40      100.00

-------------------------------------------------------------------------------
-&gt; country2 = RU

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         15       34.88       34.88
          1 |         28       65.12      100.00
------------+-----------------------------------
      Total |         43      100.00

-------------------------------------------------------------------------------
-&gt; country2 = SE

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         36       62.07       62.07
          1 |         22       37.93      100.00
------------+-----------------------------------
      Total |         58      100.00

-------------------------------------------------------------------------------
-&gt; country2 = SW

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         18       52.94       52.94
          1 |         16       47.06      100.00
------------+-----------------------------------
      Total |         34      100.00

-------------------------------------------------------------------------------
-&gt; country2 = UK

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         23       34.85       34.85
          1 |         43       65.15      100.00
------------+-----------------------------------
      Total |         66      100.00

-------------------------------------------------------------------------------
-&gt; country2 = US

     female |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         81       34.32       34.32
          1 |        155       65.68      100.00
------------+-----------------------------------
      Total |        236      100.00

. bysort country2: sum age english_prof 

-------------------------------------------------------------------------------
-&gt; country2 = BR

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         43     27.4186    8.572471         18         55
english_prof |         43    4.302326    2.087775          1          7

-------------------------------------------------------------------------------
-&gt; country2 = CA.e

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         56    23.01786    4.047406         18         40
english_prof |         56    6.785714    .5296409          5          7

-------------------------------------------------------------------------------
-&gt; country2 = CA.f

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         36    37.02778    14.13099         17         63
english_prof |         36    6.111111    1.347543          2          7

-------------------------------------------------------------------------------
-&gt; country2 = CH

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         39    37.58974    12.25973         20         66
english_prof |         39    3.051282    2.139217          1          7

-------------------------------------------------------------------------------
-&gt; country2 = CN

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         64    25.92188    4.667703         19         39
english_prof |         64    3.890625    1.481282          1          7

-------------------------------------------------------------------------------
-&gt; country2 = DK

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         41    35.21951    14.17835         21         64
english_prof |         41    5.609756    1.180636          2          7

-------------------------------------------------------------------------------
-&gt; country2 = FR

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         65    28.47692    11.28066         16         58
english_prof |         65    5.353846    1.304209          2          7

-------------------------------------------------------------------------------
-&gt; country2 = GH

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         73    31.41096    10.82799         18         71
english_prof |         74    5.662162    1.407193          1          7

-------------------------------------------------------------------------------
-&gt; country2 = IN

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         58    33.84483    8.675033         22         61
english_prof |         58    4.344828    2.164723          1          7

-------------------------------------------------------------------------------
-&gt; country2 = IS.j

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         86    24.18605    3.219469         17         35
english_prof |         86    5.930233    1.281458          1          7

-------------------------------------------------------------------------------
-&gt; country2 = IS.p

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         34          19    2.059715         16         25
english_prof |         34    5.205882    1.493002          1          7

-------------------------------------------------------------------------------
-&gt; country2 = IT

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         40      24.275    5.769004         20         57
english_prof |         40       5.625    1.314368          1          7

-------------------------------------------------------------------------------
-&gt; country2 = JP

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         43     21.5814     2.01462         18         29
english_prof |         43    3.674419    1.643471          1          7

-------------------------------------------------------------------------------
-&gt; country2 = NZ

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         39     47.5641    16.92677         21         66
english_prof |         40         6.9    .3038218          6          7

-------------------------------------------------------------------------------
-&gt; country2 = RU

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         43    32.46512    11.84493         20         61
english_prof |         43     3.27907    2.003872          1          7

-------------------------------------------------------------------------------
-&gt; country2 = SE

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         58    31.32759    9.827259         18         63
english_prof |         58    3.034483    1.815774          1          7

-------------------------------------------------------------------------------
-&gt; country2 = SW

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         34    43.52941    13.71846         24         66
english_prof |         34    5.676471    .9118941          4          7

-------------------------------------------------------------------------------
-&gt; country2 = UK

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         66     40.0303    14.28821         19         74
english_prof |         66     6.69697    .5809726          4          7

-------------------------------------------------------------------------------
-&gt; country2 = US

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |        236    25.49576    12.91395         17         69
english_prof |        236    6.915254    .3707674          3          7

. * Table 1 Last Column
. sum story11_rating3 story12_rating3 story13_rating3 story14_rating3 story15_r
&gt; ating3 story16_rating3 story17_rating3 story18_rating3

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
story11_ra~3 |        571    4.584939    1.785237          1          7
story12_ra~3 |        453    3.754967    1.686622          1          7
story13_ra~3 |        623     4.81862    1.974314          1          7
story14_ra~3 |        593    5.092749      1.8297          1          7
story15_ra~3 |        628    1.745223    1.133255          1          7
-------------+---------------------------------------------------------
story16_ra~3 |        616    1.474026    .9470402          1          7
story17_ra~3 |        563    1.321492    .9626568          1          7
story18_ra~3 |        635    1.496063    1.009997          1          7</code></pre>
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<div id="analysis-of-individual-data.dta" class="section level2">
<h2>Analysis of Individual-data.dta</h2>
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<pre class="r"><code>
M &lt;- S[,c(&quot;v_gslmc_11&quot;,&quot;v_gslmc_12&quot;,&quot;v_gslmc_13&quot;,&quot;v_gslmc_14&quot;)]
M &lt;- rowMeans(M,na.rm=T)
S$mean.neg &lt;- M

M &lt;- S[,c(&quot;v_gslmc_15&quot;,&quot;v_gslmc_16&quot;,&quot;v_gslmc_17&quot;,&quot;v_gslmc_18&quot;)]
M &lt;- rowMeans(M,na.rm=T)
S$mean.pos &lt;- M

a1 &lt;- S[,c(&quot;mean.neg&quot;,&quot;wp_right2_dichox&quot;)]
a1$tone &lt;- &quot;neg&quot;
colnames(a1) &lt;- c(&quot;gsl&quot;,&quot;lr&quot;,&quot;tone&quot;)
a2 &lt;- S[,c(&quot;mean.pos&quot;,&quot;wp_right2_dichox&quot;)]
a2$tone &lt;- &quot;pos&quot;
colnames(a2) &lt;- c(&quot;gsl&quot;,&quot;lr&quot;,&quot;tone&quot;)
A &lt;- rbind(a1,a2)
rm(a1,a2)
A$tone &lt;- as.factor(A$tone)
A$lr &lt;- as.factor(A$lr)

model1 &lt;- lm(gsl ~ lr * tone, data=A)
eff1 &lt;- effect(&quot;lr * tone&quot;,model1, typical=mean)
s &lt;- cbind(eff1$x,fit=eff1$fit,lower=eff1$lower,higher=eff1$upper)
s &lt;- s[order(s$lr,s$tone),]
s$range &lt;- c(1,2,4,5)

{
pdf(&quot;figure2.pdf&quot;, width = 7, height = 5, bg=&quot;white&quot;) 
par(mar=c(5.1,6.1,1.1,2.1))
plot(s$range,s$fit,type=&quot;n&quot;,ann=F,axes=F,xlim=c(.5,5.5),ylim=c(-.16,.08))
arrows(s$range,s$low,s$range,s$high,angle=90,length=.05,code=3,col=&quot;gray&quot;,lwd=2,lty=1)
points(s$range,s$fit,pch=15,cex=1.5)
axis(1,col=&quot;white&quot;,at=c(1,2,4,5),labels=c(&quot;Negative\n Video&quot;,&quot;Positive\n Video&quot;,&quot;Negative\n Video&quot;, &quot;Positive\n Video&quot;))
axis(2,las=1)
mtext(&quot;Mean Normalized GSL&quot;,side=2,line=4)
mtext(&quot;Left-Leaning Participants              Right-Leaning Participants&quot;,side=1,line=3)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
a1 &lt;- S[,c(&quot;mean_ph_neg_all&quot;,&quot;wp_right2_dichox&quot;)]
a1$tone &lt;- &quot;neg&quot;
colnames(a1) &lt;- c(&quot;gsl&quot;,&quot;lr&quot;,&quot;tone&quot;)
a2 &lt;- S[,c(&quot;mean_ph_pos_all&quot;,&quot;wp_right2_dichox&quot;)]
a2$tone &lt;- &quot;pos&quot;
colnames(a2) &lt;- c(&quot;gsl&quot;,&quot;lr&quot;,&quot;tone&quot;)
A &lt;- rbind(a1,a2)
rm(a1,a2)
A$tone &lt;- as.factor(A$tone)
A$lr &lt;- as.factor(A$lr)

model1 &lt;- lm(gsl ~ lr * tone, data=A)
eff1 &lt;- effect(&quot;lr * tone&quot;,model1, typical=mean)
s &lt;- cbind(eff1$x,fit=eff1$fit,lower=eff1$lower,higher=eff1$upper)
s &lt;- s[order(s$lr,s$tone),]
s$range &lt;- c(1,2,4,5)

{
pdf(&quot;figure6.pdf&quot;, width = 7, height = 5, bg=&quot;white&quot;) 
par(mar=c(5.1,6.1,1.1,2.1))
plot(s$range,s$fit,type=&quot;n&quot;,ann=F,axes=F,xlim=c(.5,5.5),ylim=c(-.05,.05))
arrows(s$range,s$low,s$range,s$high,angle=90,length=.05,code=3,col=&quot;gray&quot;,lwd=2,lty=1)
points(s$range,s$fit,pch=15,cex=1.5)
axis(1,col=&quot;white&quot;,at=c(1,2,4,5),labels=c(&quot;Negative\n Photos&quot;,&quot;Positive\n Photos&quot;,&quot;Negative\n Photos&quot;, &quot;Positive\n Photos&quot;))
axis(2,las=1)
mtext(&quot;Mean Normalized GSL&quot;,side=2,line=4)
mtext(&quot;Left-Leaning Participants              Right-Leaning Participants&quot;,side=1,line=3)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
S$right &lt;- NA
S$right[S$left_right2&lt;.5] &lt;- 0
S$right[S$left_right2==.5] &lt;- .5
S$right[S$left_right2&gt;.5] &lt;- 1
tab &lt;- RcmdrMisc::rowPercents(table(S$country2,S$right))
tab &lt;- t(tab[,c(1:3)])
tab &lt;- tab[,c(19:1)]

{
pdf(&quot;figureA1.pdf&quot;, width = 4, height = 6, bg=&quot;white&quot;) 
barplot(tab, las=1, legend.text = c(&quot;Left&quot;, &quot;Center&quot;, &quot;Right&quot;),args.legend = list(x = &quot;bottom&quot;, bty = &quot;n&quot;, inset=c(0, -.23),ncol=3), horiz=TRUE)
mtext(&quot;% Participants by Ideological Category&quot;, side=1, line=2)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
stata_src &lt;- readLines(&quot;Individual-data.do&quot;)
stata(stata_src,data.in=S)</code></pre>
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<!-- rnb-output-begin {"data":". *** Syntax for analyses of individual-level data\n. *** Use data file 'Individual-data.dta' with this syntax\n. * Figure 2\n. ttest mean_neg2==mean_pos2 if wp_right2_dichox==0\n\nPaired t test\n------------------------------------------------------------------------------\nVariable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]\n---------+--------------------------------------------------------------------\nmean_n~2 |     471   -.0240817    .0228673    .4962785   -.0690165    .0208531\nmean_p~2 |     471   -.0899855    .0252883    .5488198   -.1396775   -.0402934\n---------+--------------------------------------------------------------------\n    diff |     471    .0659037    .0320919    .6964764    .0028423    .1289652\n------------------------------------------------------------------------------\n     mean(diff) = mean(mean_neg2 - mean_pos2)                     t =   2.0536\n Ho: mean(diff) = 0                              degrees of freedom =      470\n\n Ha: mean(diff) < 0           Ha: mean(diff) != 0           Ha: mean(diff) > 0\n Pr(T < t) = 0.9797         Pr(|T| > |t|) = 0.0406          Pr(T > t) = 0.0203\n. ttest mean_neg2==mean_pos2 if wp_right2_dichox==1\n\nPaired t test\n------------------------------------------------------------------------------\nVariable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]\n---------+--------------------------------------------------------------------\nmean_n~2 |     463    .0213809    .0200558    .4315483   -.0180309    .0607927\nmean_p~2 |     463   -.0680617    .0215774    .4642906   -.1104637   -.0256597\n---------+--------------------------------------------------------------------\n    diff |     463    .0894426    .0259995    .5594429    .0383506    .1405346\n------------------------------------------------------------------------------\n     mean(diff) = mean(mean_neg2 - mean_pos2)                     t =   3.4402\n Ho: mean(diff) = 0                              degrees of freedom =      462\n\n Ha: mean(diff) < 0           Ha: mean(diff) != 0           Ha: mean(diff) > 0\n Pr(T < t) = 0.9997         Pr(|T| > |t|) = 0.0006          Pr(T > t) = 0.0003\n. ttest mean_dif2, by(wp_right2_dichox)\n\nTwo-sample t test with equal variances\n------------------------------------------------------------------------------\n   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]\n---------+--------------------------------------------------------------------\n       0 |     471    .0659037    .0320919    .6964764    .0028423    .1289652\n       1 |     463    .0894426    .0259995    .5594429    .0383506    .1405346\n---------+--------------------------------------------------------------------\ncombined |     934    .0775724     .020681    .6320417    .0369856    .1181591\n---------+--------------------------------------------------------------------\n    diff |           -.0235389    .0413786               -.1047449    .0576671\n------------------------------------------------------------------------------\n    diff = mean(0) - mean(1)                                      t =  -0.5689\nHo: diff = 0                                     degrees of freedom =      932\n\n    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0\n Pr(T < t) = 0.2848         Pr(|T| > |t|) = 0.5696          Pr(T > t) = 0.7152\n. * Table 2\n. quietly regress mean_dif2 wp_right2 female age income university \n. estimates store A\n. esttab A , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)\n\n----------------------------\n                      (1)   \n                mean_dif2   \n                     b/se   \n----------------------------\nwp_right2           0.104   \n                  (0.093)   \nfemale             -0.023   \n                  (0.042)   \nage                -0.003   \n                  (0.002)   \nincome              0.086   \n                  (0.088)   \nuniversity         -0.054   \n                  (0.044)   \n_cons               0.131   \n                  (0.093)   \n----------------------------\nr2                  0.007   \nr2_a                0.002   \nN                 933.000   \n----------------------------\n. regress mean_dif2 wp_right2 female age income university, beta\n\n      Source |       SS           df       MS      Number of obs   =       933\n-------------+----------------------------------   F(5, 927)       =      1.34\n       Model |   2.6843355         5    .5368671   Prob > F        =    0.2430\n    Residual |  370.026446       927  .399165529   R-squared       =    0.0072\n-------------+----------------------------------   Adj R-squared   =    0.0018\n       Total |  372.710781       932  .399904272   Root MSE        =     .6318\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|                     Beta\n-------------+----------------------------------------------------------------\n   wp_right2 |   .1035859    .093023     1.11   0.266                  .036934\n      female |  -.0230074   .0418745    -0.55   0.583                -.0181692\n         age |  -.0031561   .0017191    -1.84   0.067                 -.061052\n      income |   .0856957   .0881939     0.97   0.331                 .0318768\n  university |  -.0540114   .0442642    -1.22   0.223                -.0405662\n       _cons |    .130539   .0926448     1.41   0.159                        .\n------------------------------------------------------------------------------\n. egen wp2 = std(wp_right2)\n. egen md2 = std(mean_dif2)\n. regress md2 wp2 female age income university\n\n      Source |       SS           df       MS      Number of obs   =       933\n-------------+----------------------------------   F(5, 927)       =      1.34\n       Model |  6.71963057         5  1.34392611   Prob > F        =    0.2430\n    Residual |  926.278036       927  .999221182   R-squared       =    0.0072\n-------------+----------------------------------   Adj R-squared   =    0.0018\n       Total |  932.997666       932  1.00107046   Root MSE        =    .99961\n\n------------------------------------------------------------------------------\n         md2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n         wp2 |   .0369852   .0332137     1.11   0.266    -.0281976    .1021679\n      female |  -.0364017   .0662528    -0.55   0.583    -.1664246    .0936211\n         age |  -.0049935   .0027199    -1.84   0.067    -.0103313    .0003443\n      income |   .1355856    .139538     0.97   0.331    -.1382615    .4094327\n  university |  -.0854555   .0700337    -1.22   0.223    -.2228985    .0519876\n       _cons |   .1473403   .1319921     1.12   0.265    -.1116976    .4063783\n------------------------------------------------------------------------------\n. * Figure 6\n. ttest mean_ph_neg_all==mean_ph_pos_all if wp_right2_dichox==0\n\nPaired t test\n------------------------------------------------------------------------------\nVariable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]\n---------+--------------------------------------------------------------------\nme~g_all |     411    .0275029     .007584     .153752    .0125945    .0424114\nme~s_all |     411   -.0169125    .0071241     .144427   -.0309167   -.0029082\n---------+--------------------------------------------------------------------\n    diff |     411    .0444154    .0107432    .2177983    .0232968     .065534\n------------------------------------------------------------------------------\n     mean(diff) = mean(mean_ph_neg_all - mean_ph_pos_all)         t =   4.1343\n Ho: mean(diff) = 0                              degrees of freedom =      410\n\n Ha: mean(diff) < 0           Ha: mean(diff) != 0           Ha: mean(diff) > 0\n Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000\n. ttest mean_ph_neg_all==mean_ph_pos_all if wp_right2_dichox==1\n\nPaired t test\n------------------------------------------------------------------------------\nVariable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]\n---------+--------------------------------------------------------------------\nme~g_all |     396    .0074071    .0073337    .1459391   -.0070109    .0218251\nme~s_all |     396   -.0162411    .0060894    .1211766   -.0282127   -.0042695\n---------+--------------------------------------------------------------------\n    diff |     396    .0236482     .010401    .2069764       .0032    .0440963\n------------------------------------------------------------------------------\n     mean(diff) = mean(mean_ph_neg_all - mean_ph_pos_all)         t =   2.2737\n Ho: mean(diff) = 0                              degrees of freedom =      395\n\n Ha: mean(diff) < 0           Ha: mean(diff) != 0           Ha: mean(diff) > 0\n Pr(T < t) = 0.9882         Pr(|T| > |t|) = 0.0235          Pr(T > t) = 0.0118\n. ttest mean_ph_dif_all, by(wp_right2_dichox)\n\nTwo-sample t test with equal variances\n------------------------------------------------------------------------------\n   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]\n---------+--------------------------------------------------------------------\n       0 |     411    .0444154    .0107432    .2177983    .0232968     .065534\n       1 |     396    .0236482     .010401    .2069764       .0032    .0440963\n---------+--------------------------------------------------------------------\ncombined |     807    .0342248    .0074867     .212679    .0195291    .0489204\n---------+--------------------------------------------------------------------\n    diff |            .0207672    .0149673               -.0086124    .0501468\n------------------------------------------------------------------------------\n    diff = mean(0) - mean(1)                                      t =   1.3875\nHo: diff = 0                                     degrees of freedom =      805\n\n    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0\n Pr(T < t) = 0.9172         Pr(|T| > |t|) = 0.1657          Pr(T > t) = 0.0828\n. * Table 5 Column 1\n. quietly regress mean_ph_dif_all wp_right2 female age income university  \n. estimates store A\n. esttab A , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)\n\n----------------------------\n                      (1)   \n             mean_p~f_all   \n                     b/se   \n----------------------------\nwp_right2          -0.069*  \n                  (0.034)   \nfemale              0.031*  \n                  (0.015)   \nage                -0.000   \n                  (0.001)   \nincome             -0.026   \n                  (0.032)   \nuniversity          0.002   \n                  (0.016)   \n_cons               0.073*  \n                  (0.033)   \n----------------------------\nr2                  0.013   \nr2_a                0.007   \nN                 806.000   \n----------------------------\n. regress mean_ph_dif_all wp_right2 female age income university, beta\n\n      Source |       SS           df       MS      Number of obs   =       806\n-------------+----------------------------------   F(5, 800)       =      2.06\n       Model |  .464167318         5  .092833464   Prob > F        =    0.0679\n    Residual |  35.9916953       800  .044989619   R-squared       =    0.0127\n-------------+----------------------------------   Adj R-squared   =    0.0066\n       Total |  36.4558626       805  .045286786   Root MSE        =    .21211\n\n------------------------------------------------------------------------------\nmean_p~f_all |      Coef.   Std. Err.      t    P>|t|                     Beta\n-------------+----------------------------------------------------------------\n   wp_right2 |   -.069114   .0340791    -2.03   0.043                -.0720893\n      female |    .030908   .0150366     2.06   0.040                 .0726639\n         age |  -.0004451   .0005922    -0.75   0.452                -.0266983\n      income |  -.0256898   .0320628    -0.80   0.423                -.0282353\n  university |   .0017661   .0156791     0.11   0.910                  .004003\n       _cons |    .072752   .0333775     2.18   0.030                        .\n------------------------------------------------------------------------------\n. egen mp2 = std(mean_ph_dif_all)\n(127 missing values generated)\n. regress mp2 wp2 female age income university \n\n      Source |       SS           df       MS      Number of obs   =       806\n-------------+----------------------------------   F(5, 800)       =      2.06\n       Model |  10.2618427         5  2.05236853   Prob > F        =    0.0679\n    Residual |  795.706839       800  .994633549   R-squared       =    0.0127\n-------------+----------------------------------   Adj R-squared   =    0.0066\n       Total |  805.968682       805  1.00120333   Root MSE        =    .99731\n\n------------------------------------------------------------------------------\n         mp2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n         wp2 |  -.0733355   .0361606    -2.03   0.043    -.1443164   -.0023545\n      female |   .1453268   .0707009     2.06   0.040     .0065455     .284108\n         age |  -.0020927   .0027843    -0.75   0.453     -.007558    .0033726\n      income |  -.1207916   .1507566    -0.80   0.423    -.4167168    .1751335\n  university |    .008304   .0737218     0.11   0.910    -.1364069    .1530149\n       _cons |    .055167    .139366     0.40   0.692    -.2183993    .3287333\n------------------------------------------------------------------------------\n. * Appendix Ideology Alphas\n. alpha wp_abortion wp_capitalism wp_gaymarriage wp_guncontrol wp_milspend wp_p\n> atriotism wp_socialism if country2==\"BR\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0304323\nNumber of items in the scale:            7\nScale reliability coefficient:      0.6440\n. alpha wp_abortion wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_mil\n> spend wp_obedience wp_patriotism wp_socialism wp_taxcuts if country2==\"CA.e\" \n> | country2==\"CA.f\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0398736\nNumber of items in the scale:           10\nScale reliability coefficient:      0.8025\n. alpha wp_abortion wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_imm\n> igration wp_milspend wp_obedience wp_patriotism wp_socialism if country2==\"CH\n> \"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0356349\nNumber of items in the scale:           10\nScale reliability coefficient:      0.7473\n. alpha wp_cencorship wp_obedience wp_patriotism wp_women if country2==\"CN\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0109147\nNumber of items in the scale:            4\nScale reliability coefficient:      0.3610\n. alpha wp_capitalism wp_deathp wp_guncontrol wp_immigration wp_milspend wp_obe\n> dience wp_pollution wp_socialism wp_taxcuts if country2==\"DK\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0237862\nNumber of items in the scale:            9\nScale reliability coefficient:      0.6345\n. alpha wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_immigration wp_\n> milspend wp_obedience wp_patriotism wp_pollution wp_socialism wp_taxcuts wp_w\n> omen if country2==\"FR\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:      .030893\nNumber of items in the scale:           12\nScale reliability coefficient:      0.7698\n. alpha wp_deathp wp_gaymarriage wp_obedience wp_patriotism wp_taxcuts if count\n> ry2==\"GH\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:      .009259\nNumber of items in the scale:            5\nScale reliability coefficient:      0.3697\n. alpha wp_abortion wp_cencorship wp_deathp wp_gaymarriage wp_milspend wp_obedi\n> ence wp_patriotism wp_taxcuts if country2==\"IN\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0368594\nNumber of items in the scale:            8\nScale reliability coefficient:      0.6978\n. alpha wp_abortion wp_cencorship wp_gaymarriage wp_immigration wp_milspend wp_\n> women if country2==\"IS.j\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0305129\nNumber of items in the scale:            6\nScale reliability coefficient:      0.6705\n. alpha wp_abortion wp_deathp wp_gaymarriage wp_immigration wp_milspend wp_patr\n> iotism wp_socialism if country2==\"IS.p\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0260276\nNumber of items in the scale:            7\nScale reliability coefficient:      0.5707\n. alpha wp_abortion wp_capitalism wp_cencorship wp_deathp wp_immigration wp_mil\n> spend wp_obedience wp_patriotism wp_pollution wp_women if country2==\"IT\"\nwp_pollution wp_women constant in analysis sample, dropped from analysis\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0275767\nNumber of items in the scale:            8\nScale reliability coefficient:      0.6747\n. alpha wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_immigration wp_\n> obedience wp_patriotism wp_women if country2==\"JP\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:      .022697\nNumber of items in the scale:            8\nScale reliability coefficient:      0.6484\n. alpha wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_milspend wp_obe\n> dience wp_patriotism wp_pollution wp_socialism wp_taxcuts if country2==\"NZ\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0391969\nNumber of items in the scale:           10\nScale reliability coefficient:      0.7596\n. alpha wp_abortion wp_cencorship wp_gaymarriage wp_obedience wp_patriotism wp_\n> taxcuts if country2==\"RU\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0525538\nNumber of items in the scale:            6\nScale reliability coefficient:      0.7771\n. alpha wp_cencorship wp_obedience wp_patriotism wp_taxcuts if country2==\"SE\"  \n>    \n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:      .019559\nNumber of items in the scale:            4\nScale reliability coefficient:      0.3975\n. alpha wp_capitalism wp_deathp wp_gaymarriage wp_guncontrol wp_immigration wp_\n> milspend wp_obedience wp_patriotism wp_socialism wp_taxcuts if country2==\"SW\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0547762\nNumber of items in the scale:           10\nScale reliability coefficient:      0.8316\n. alpha wp_abortion wp_capitalism wp_cencorship wp_gaymarriage wp_immigration w\n> p_milspend wp_obedience wp_patriotism wp_taxcuts wp_women if country2==\"UK\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0270316\nNumber of items in the scale:           10\nScale reliability coefficient:      0.7088\n. alpha wp_abortion wp_capitalism wp_deathp wp_gaymarriage wp_guncontrol wp_imm\n> igration wp_milspend wp_obedience wp_patriotism wp_pollution wp_socialism wp_\n> taxcuts if country2==\"US\"\n\nTest scale = mean(unstandardized items)\n\nAverage interitem covariance:     .0327332\nNumber of items in the scale:           12\nScale reliability coefficient:      0.7766\n.   \n.   \n. * Figure A1\n. gen left_right3 = .\n(934 missing values generated)\n. replace left_right3 = 0 if left_right2 < .5 & left_right2~=.\n(402 real changes made)\n. replace left_right3 = .5 if left_right2==.5 & left_right2~=.\n(181 real changes made)\n. replace left_right3 = 1 if left_right2 > .5 & left_right2~=.\n(350 real changes made)\n. bysort country2: tab left_right3\n\n-------------------------------------------------------------------------------\n-> country2 = BR\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         15       42.86       42.86\n         .5 |          8       22.86       65.71\n          1 |         12       34.29      100.00\n------------+-----------------------------------\n      Total |         35      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CA.e\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         22       68.75       68.75\n         .5 |          6       18.75       87.50\n          1 |          4       12.50      100.00\n------------+-----------------------------------\n      Total |         32      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CA.f\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         20       74.07       74.07\n         .5 |          1        3.70       77.78\n          1 |          6       22.22      100.00\n------------+-----------------------------------\n      Total |         27      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CH\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         19       52.78       52.78\n         .5 |         13       36.11       88.89\n          1 |          4       11.11      100.00\n------------+-----------------------------------\n      Total |         36      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = CN\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |          4        7.14        7.14\n         .5 |          5        8.93       16.07\n          1 |         47       83.93      100.00\n------------+-----------------------------------\n      Total |         56      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = DK\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         19       54.29       54.29\n         .5 |          5       14.29       68.57\n          1 |         11       31.43      100.00\n------------+-----------------------------------\n      Total |         35      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = FR\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         22       43.14       43.14\n         .5 |          4        7.84       50.98\n          1 |         25       49.02      100.00\n------------+-----------------------------------\n      Total |         51      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = GH\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |          5        8.33        8.33\n         .5 |         25       41.67       50.00\n          1 |         30       50.00      100.00\n------------+-----------------------------------\n      Total |         60      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IN\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         14       28.00       28.00\n         .5 |         12       24.00       52.00\n          1 |         24       48.00      100.00\n------------+-----------------------------------\n      Total |         50      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IS.j\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         30       42.25       42.25\n         .5 |          7        9.86       52.11\n          1 |         34       47.89      100.00\n------------+-----------------------------------\n      Total |         71      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IS.p\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |          2        6.25        6.25\n         .5 |          4       12.50       18.75\n          1 |         26       81.25      100.00\n------------+-----------------------------------\n      Total |         32      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = IT\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         21       56.76       56.76\n         .5 |          4       10.81       67.57\n          1 |         12       32.43      100.00\n------------+-----------------------------------\n      Total |         37      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = JP\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         15       41.67       41.67\n         .5 |         12       33.33       75.00\n          1 |          9       25.00      100.00\n------------+-----------------------------------\n      Total |         36      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = NZ\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         21       65.62       65.62\n         .5 |          3        9.38       75.00\n          1 |          8       25.00      100.00\n------------+-----------------------------------\n      Total |         32      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = RU\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |          9       28.12       28.12\n         .5 |         19       59.38       87.50\n          1 |          4       12.50      100.00\n------------+-----------------------------------\n      Total |         32      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = SE\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         19       39.58       39.58\n         .5 |         15       31.25       70.83\n          1 |         14       29.17      100.00\n------------+-----------------------------------\n      Total |         48      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = SW\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         15       48.39       48.39\n         .5 |          3        9.68       58.06\n          1 |         13       41.94      100.00\n------------+-----------------------------------\n      Total |         31      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = UK\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |         25       52.08       52.08\n         .5 |         15       31.25       83.33\n          1 |          8       16.67      100.00\n------------+-----------------------------------\n      Total |         48      100.00\n\n-------------------------------------------------------------------------------\n-> country2 = US\n\nleft_right3 |      Freq.     Percent        Cum.\n------------+-----------------------------------\n          0 |        105       57.07       57.07\n         .5 |         20       10.87       67.93\n          1 |         59       32.07      100.00\n------------+-----------------------------------\n      Total |        184      100.00\n\n.   \n. * Table A1\n. sum age female income university english_prof wp_right2\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |        933    29.18435    12.23282         16         74\n      female |        934    .5299786    .4993679          0          1\n      income |        934    .5444326     .235109          0          1\n  university |        934    .6573876    .4748374          0          1\nenglish_prof |        934    5.392934    1.888872          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |        934    .3876842    .2256694          0   .8888889\n. bysort country2: sum age female income university english_prof wp_right2\n\n-------------------------------------------------------------------------------\n-> country2 = BR\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         35    25.57143     5.68427         18         42\n      female |         35    .5714286    .5020964          0          1\n      income |         35    .5619048    .2289708          0          1\n  university |         35    .6857143    .4710082          0          1\nenglish_prof |         35    4.085714    2.119537          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         35    .3589286    .1889301          0        .75\n\n-------------------------------------------------------------------------------\n-> country2 = CA.e\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         32    22.90625    4.357858         18         40\n      female |         32       .6875    .4709291          0          1\n      income |         32    .5052083     .248596          0          1\n  university |         32        .875    .3360108          0          1\nenglish_prof |         32     6.78125    .5526695          5          7\n-------------+---------------------------------------------------------\n   wp_right2 |         32    .2197917    .1917137          0         .8\n\n-------------------------------------------------------------------------------\n-> country2 = CA.f\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         27    35.14815    13.88054         17         63\n      female |         27    .2962963    .4653216          0          1\n      income |         27    .5432099    .2147976   .1666667   .8333333\n  university |         27    .7777778    .4236593          0          1\nenglish_prof |         27    6.222222    1.187542          3          7\n-------------+---------------------------------------------------------\n   wp_right2 |         27     .252862    .2171309          0   .7272727\n\n-------------------------------------------------------------------------------\n-> country2 = CH\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         36    36.88889    12.42987         20         66\n      female |         36          .5    .5070926          0          1\n      income |         36    .4074074    .1844961   .1666667   .8333333\n  university |         36    .5833333          .5          0          1\nenglish_prof |         36    3.222222    2.139574          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         36    .3131313    .1985121          0   .7727273\n\n-------------------------------------------------------------------------------\n-> country2 = CN\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         56    26.03571    4.805165         19         39\n      female |         56    .4821429    .5042031          0          1\n      income |         56    .4434524    .1914242          0          1\n  university |         56        .875    .3337119          0          1\nenglish_prof |         56       3.875    1.549927          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         56    .4946429    .1380641          0         .7\n\n-------------------------------------------------------------------------------\n-> country2 = DK\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         35    34.57143    14.44317         21         64\n      female |         35          .4    .4970501          0          1\n      income |         35    .5952381    .2187521          0          1\n  university |         35    .6857143    .4710082          0          1\nenglish_prof |         35    5.514286    1.221653          2          7\n-------------+---------------------------------------------------------\n   wp_right2 |         35    .2914286    .1742571        .05         .6\n\n-------------------------------------------------------------------------------\n-> country2 = FR\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         51     27.2549    10.47634         16         58\n      female |         51    .4901961    .5048782          0          1\n      income |         51     .627451    .2175322          0          1\n  university |         51    .5098039    .5048782          0          1\nenglish_prof |         51    5.411765    1.251822          2          7\n-------------+---------------------------------------------------------\n   wp_right2 |         51    .3556435    .1841998   .0384615   .7692308\n\n-------------------------------------------------------------------------------\n-> country2 = GH\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         60       31.05    10.42881         18         67\n      female |         61    .5409836     .502453          0          1\n      income |         61    .5218579    .2480954          0          1\n  university |         61    .4918033    .5040817          0          1\nenglish_prof |         61    5.540984    1.455722          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         61     .629235    .1738895          0   .8333333\n\n-------------------------------------------------------------------------------\n-> country2 = IN\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         50       33.16    8.266875         22         53\n      female |         50          .4    .4948717          0          1\n      income |         50    .4933333    .2607333          0          1\n  university |         50         .38    .4903144          0          1\nenglish_prof |         50           4    2.118914          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         50    .6031944    .2190013          0   .8888889\n\n-------------------------------------------------------------------------------\n-> country2 = IS.j\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         71    23.94366    3.134542         17         33\n      female |         71    .5070423    .5035088          0          1\n      income |         71    .5798122    .2161333          0          1\n  university |         71    .8591549    .3503376          0          1\nenglish_prof |         71    5.957746    1.235622          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         71    .2194836    .1827042          0   .7142857\n\n-------------------------------------------------------------------------------\n-> country2 = IS.p\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         32          19    2.109885         16         25\n      female |         32      .59375    .4989909          0          1\n      income |         32       .4375    .2148184          0   .8333333\n  university |         32       .9375    .2459347          0          1\nenglish_prof |         32      5.1875    1.533234          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         32    .3560268    .1874486          0       .875\n\n-------------------------------------------------------------------------------\n-> country2 = IT\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         37    24.35135    5.954532         20         57\n      female |         37    .6756757     .474579          0          1\n      income |         37    .5720721    .1645258   .1666667   .8333333\n  university |         37    .8918919    .3148001          0          1\nenglish_prof |         37    5.567568    1.344547          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         37    .2444717    .1470366          0         .5\n\n-------------------------------------------------------------------------------\n-> country2 = JP\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         36        21.5    1.664761         18         26\n      female |         36    .4444444    .5039526          0          1\n      income |         36    .5324074    .2482301          0          1\n  university |         36    .8888889    .3187276          0          1\nenglish_prof |         36         3.5    1.594634          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         36    .3503086    .1663062          0   .7777778\n\n-------------------------------------------------------------------------------\n-> country2 = NZ\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         32    45.65625    17.70112         21         66\n      female |         32       .4375    .5040161          0          1\n      income |         32        .625    .2710659          0          1\n  university |         32       .6875    .4709291          0          1\nenglish_prof |         32      6.9375    .2459347          6          7\n-------------+---------------------------------------------------------\n   wp_right2 |         32    .3210227    .2065114          0   .7272727\n\n-------------------------------------------------------------------------------\n-> country2 = RU\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         32     29.9375    10.11526         20         59\n      female |         32      .59375    .4989909          0          1\n      income |         32      .40625    .1982789          0   .6666667\n  university |         32        .875    .3360108          0          1\nenglish_prof |         32       3.625    1.979736          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         32    .5669643    .2228972          0   .8571429\n\n-------------------------------------------------------------------------------\n-> country2 = SE\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         48    31.04167    10.09942         18         63\n      female |         48    .3333333    .4763931          0          1\n      income |         48    .5104167    .1627419          0          1\n  university |         48    .3541667    .4833211          0          1\nenglish_prof |         48    2.833333    1.667376          1          7\n-------------+---------------------------------------------------------\n   wp_right2 |         48          .6    .1774524         .2         .8\n\n-------------------------------------------------------------------------------\n-> country2 = SW\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         31    44.22581    13.72032         24         66\n      female |         31    .4516129    .5058794          0          1\n      income |         31    .6344086     .203758   .1666667          1\n  university |         31    .6129032    .4951376          0          1\nenglish_prof |         31    5.645161    .9146361          4          7\n-------------+---------------------------------------------------------\n   wp_right2 |         31    .3197947    .2332503          0   .8181818\n\n-------------------------------------------------------------------------------\n-> country2 = UK\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |         48    40.83333    14.97421         19         74\n      female |         48        .625    .4892461          0          1\n      income |         48    .4826389    .2484933          0          1\n  university |         48    .2291667    .4247444          0          1\nenglish_prof |         48    6.791667    .5441501          4          7\n-------------+---------------------------------------------------------\n   wp_right2 |         48    .2989583    .1877894          0        .65\n\n-------------------------------------------------------------------------------\n-> country2 = US\n\n    Variable |        Obs        Mean    Std. Dev.       Min        Max\n-------------+---------------------------------------------------------\n         age |        184    24.57609    11.81528         17         68\n      female |        184    .6467391    .4792871          0          1\n      income |        184     .615942    .2460855          0          1\n  university |        184    .6467391    .4792871          0          1\nenglish_prof |        184    6.918478    .3895996          3          7\n-------------+---------------------------------------------------------\n   wp_right2 |        184    .3788496    .1894891   .0384615   .8846154\n\n. * Table A3 Row 1\n. quietly regress mean_dif2 wp_right2 female age income university \n. estimates store A\n. quietly regress mean_dif3 wp_right2 female age income university \n. estimates store B\n. esttab A B , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)\n\n--------------------------------------------\n                      (1)             (2)   \n                mean_dif2       mean_dif3   \n                     b/se            b/se   \n--------------------------------------------\nwp_right2           0.104          -0.172   \n                  (0.093)         (0.157)   \nfemale             -0.023          -0.016   \n                  (0.042)         (0.071)   \nage                -0.003          -0.002   \n                  (0.002)         (0.003)   \nincome              0.086          -0.061   \n                  (0.088)         (0.149)   \nuniversity         -0.054           0.015   \n                  (0.044)         (0.075)   \n_cons               0.131           0.152   \n                  (0.093)         (0.157)   \n--------------------------------------------\nr2                  0.007           0.002   \nr2_a                0.002          -0.003   \nN                 933.000         933.000   \n--------------------------------------------\n.   \n. * Table A4 Row 1 \n. quietly regress mean_ph_dif_all wp_right2 female age income university  \n. estimates store A\n. quietly regress mean_ph_dif3_all wp_right2 female age income university  \n. estimates store B\n. quietly regress mean_ph_dif2_all wp_right2 female age income university  \n. estimates store C\n. esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n             mean_p~f_all    mean_p~3_all    mean_p~2_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nwp_right2          -0.069*         -0.074          -0.053   \n                  (0.034)         (0.042)         (0.042)   \nfemale              0.031*          0.027           0.042*  \n                  (0.015)         (0.018)         (0.019)   \nage                -0.000          -0.001          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.026          -0.009          -0.059   \n                  (0.032)         (0.039)         (0.039)   \nuniversity          0.002           0.010          -0.004   \n                  (0.016)         (0.019)         (0.019)   \n_cons               0.073*          0.068           0.077   \n                  (0.033)         (0.041)         (0.041)   \n------------------------------------------------------------\nr2                  0.013           0.009           0.012   \nr2_a                0.007           0.003           0.005   \nN                 806.000         795.000         796.000   \n------------------------------------------------------------\n.                 \n. * Table A6 Row 1\n.   \n.   gen right2 = .\n(934 missing values generated)\n.   replace right2= wp_right2\n(934 real changes made)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store A\n.   replace right2= wp_right2_dicho2\n(890 real changes made)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store B  \n.   replace right2= wp_right2_dichox\n(264 real changes made)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store C\n.   replace right2= left_right2\n(879 real changes made, 1 to missing)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store D\n.   replace right2= left_right2_dichox\n(841 real changes made)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store E \n.   replace right2= ideo_right2\n(929 real changes made)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store F\n.   replace right2= ideo_right2_dichox\n(929 real changes made)\n.   quietly regress mean_dif2 right2 female age income university  \n.   estimates store G  \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)  \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                mean_dif2       mean_dif2       mean_dif2   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nright2              0.104           0.006           0.022   \n                  (0.093)         (0.044)         (0.042)   \nfemale             -0.023          -0.025          -0.024   \n                  (0.042)         (0.042)         (0.042)   \nage                -0.003          -0.003          -0.003   \n                  (0.002)         (0.002)         (0.002)   \nincome              0.086           0.081           0.078   \n                  (0.088)         (0.088)         (0.088)   \nuniversity         -0.054          -0.060          -0.059   \n                  (0.044)         (0.044)         (0.044)   \n_cons               0.131           0.173*          0.166   \n                  (0.093)         (0.085)         (0.085)   \n------------------------------------------------------------\nr2_w                                                        \nr2_b                                                        \nr2_o                                                        \nN                 933.000         933.000         933.000   \nN_g                                                         \n------------------------------------------------------------\n.   esttab D E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g)  \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                mean_dif2       mean_dif2       mean_dif2       mean_dif2   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nright2              0.100           0.052           0.144           0.104*  \n                  (0.080)         (0.042)         (0.102)         (0.041)   \nfemale             -0.022          -0.024          -0.022          -0.023   \n                  (0.042)         (0.042)         (0.042)         (0.042)   \nage                -0.003          -0.003          -0.003          -0.003   \n                  (0.002)         (0.002)         (0.002)         (0.002)   \nincome              0.078           0.073           0.082           0.071   \n                  (0.088)         (0.088)         (0.088)         (0.088)   \nuniversity         -0.059          -0.057          -0.055          -0.055   \n                  (0.044)         (0.044)         (0.044)         (0.044)   \n_cons               0.125           0.151           0.108           0.128   \n                  (0.093)         (0.086)         (0.097)         (0.085)   \n----------------------------------------------------------------------------\nr2_w                                                                        \nr2_b                                                                        \nr2_o                                                                        \nN                 932.000         932.000         932.000         932.000   \nN_g                                                                         \n----------------------------------------------------------------------------\n.   \n.   \n. * Table A6 Row 4 \n.   replace right2= wp_right2\n(898 real changes made)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store A\n.   replace right2= wp_right2_dicho2\n(890 real changes made)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store B\n.   replace right2= wp_right2_dichox\n(264 real changes made)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store C\n.   replace right2= left_right2\n(879 real changes made, 1 to missing)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store D  \n.   replace right2= left_right2_dichox\n(841 real changes made)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store E\n.   replace right2= ideo_right2\n(929 real changes made)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store F\n.   replace right2= ideo_right2_dichox\n(929 real changes made)\n.   quietly regress mean_ph_dif_all right2 female age income university  \n.   estimates store G\n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)  \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n             mean_p~f_all    mean_p~f_all    mean_p~f_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nright2             -0.069*         -0.037*         -0.018   \n                  (0.034)         (0.016)         (0.015)   \nfemale              0.031*          0.030*          0.031*  \n                  (0.015)         (0.015)         (0.015)   \nage                -0.000          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.026          -0.027          -0.019   \n                  (0.032)         (0.032)         (0.032)   \nuniversity          0.002           0.003           0.005   \n                  (0.016)         (0.016)         (0.016)   \n_cons               0.073*          0.058           0.049   \n                  (0.033)         (0.030)         (0.030)   \n------------------------------------------------------------\nr2_w                                                        \nr2_b                                                        \nr2_o                                                        \nN                 806.000         806.000         806.000   \nN_g                                                         \n------------------------------------------------------------\n.   esttab D E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g)  \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n             mean_p~f_all    mean_p~f_all    mean_p~f_all    mean_p~f_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nright2             -0.041           0.013          -0.074*         -0.012   \n                  (0.029)         (0.015)         (0.037)         (0.015)   \nfemale              0.031*          0.032*          0.031*          0.032*  \n                  (0.015)         (0.015)         (0.015)         (0.015)   \nage                -0.001          -0.001          -0.001          -0.000   \n                  (0.001)         (0.001)         (0.001)         (0.001)   \nincome             -0.020          -0.023          -0.023          -0.020   \n                  (0.032)         (0.032)         (0.032)         (0.032)   \nuniversity          0.005           0.006           0.003           0.004   \n                  (0.016)         (0.016)         (0.016)         (0.016)   \n_cons               0.063           0.035           0.078*          0.047   \n                  (0.033)         (0.030)         (0.035)         (0.030)   \n----------------------------------------------------------------------------\nr2_w                                                                        \nr2_b                                                                        \nr2_o                                                                        \nN                 805.000         805.000         805.000         805.000   \nN_g                                                                         \n----------------------------------------------------------------------------\n.          \n.  \n. * Table A7\n.   \n. regress mean_dif2 wp_right2 female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       933\n-------------+----------------------------------   F(5, 927)       =      1.34\n       Model |   2.6843355         5    .5368671   Prob > F        =    0.2430\n    Residual |  370.026446       927  .399165529   R-squared       =    0.0072\n-------------+----------------------------------   Adj R-squared   =    0.0018\n       Total |  372.710781       932  .399904272   Root MSE        =     .6318\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n   wp_right2 |   .1035859    .093023     1.11   0.266    -.0789742     .286146\n      female |  -.0230074   .0418745    -0.55   0.583    -.1051873    .0591724\n         age |  -.0031561   .0017191    -1.84   0.067    -.0065298    .0002176\n      income |   .0856957   .0881939     0.97   0.331     -.087387    .2587785\n  university |  -.0540114   .0442642    -1.22   0.223    -.1408811    .0328583\n       _cons |    .130539   .0926448     1.41   0.159    -.0512788    .3123568\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_abortion female age income university   \n\n      Source |       SS           df       MS      Number of obs   =       927\n-------------+----------------------------------   F(5, 921)       =      1.18\n       Model |  2.36393206         5  .472786412   Prob > F        =    0.3184\n    Residual |  369.883365       921  .401610603   R-squared       =    0.0064\n-------------+----------------------------------   Adj R-squared   =    0.0010\n       Total |  372.247297       926  .401994922   Root MSE        =    .63373\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n wp_abortion |   .0312297   .0491651     0.64   0.525     -.065259    .1277183\n      female |  -.0259391    .042091    -0.62   0.538    -.1085446    .0566664\n         age |  -.0030929   .0017256    -1.79   0.073    -.0064795    .0002936\n      income |   .0856217   .0887781     0.96   0.335    -.0886093    .2598526\n  university |   -.057719   .0444389    -1.30   0.194    -.1449323    .0294942\n       _cons |   .1629146    .086651     1.88   0.060    -.0071417    .3329709\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_capitalism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       925\n-------------+----------------------------------   F(5, 919)       =      1.07\n       Model |  2.15738906         5  .431477812   Prob > F        =    0.3738\n    Residual |   369.54926       919  .402121066   R-squared       =    0.0058\n-------------+----------------------------------   Adj R-squared   =    0.0004\n       Total |  371.706649       924  .402279923   Root MSE        =    .63413\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_capital~m |   .0080723     .05153     0.16   0.876    -.0930578    .1092024\n      female |  -.0250712    .042318    -0.59   0.554    -.1081223    .0579799\n         age |  -.0030484   .0017252    -1.77   0.078    -.0064341    .0003373\n      income |   .0807063   .0903861     0.89   0.372    -.0966808    .2580935\n  university |  -.0580861   .0444095    -1.31   0.191    -.1452419    .0290697\n       _cons |   .1694028   .0867478     1.95   0.051    -.0008439    .3396496\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_cencorship female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       922\n-------------+----------------------------------   F(5, 916)       =      1.32\n       Model |  2.65212649         5  .530425298   Prob > F        =    0.2544\n    Residual |  368.913301       916  .402743778   R-squared       =    0.0071\n-------------+----------------------------------   Adj R-squared   =    0.0017\n       Total |  371.565427       921  .403436946   Root MSE        =    .63462\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_cencors~p |  -.0547273   .0495933    -1.10   0.270    -.1520569    .0426023\n      female |  -.0235865   .0423143    -0.56   0.577    -.1066307    .0594577\n         age |  -.0032203   .0017339    -1.86   0.064    -.0066232    .0001826\n      income |   .0741825   .0894133     0.83   0.407    -.1012963    .2496612\n  university |   -.059936   .0445637    -1.34   0.179    -.1473948    .0275227\n       _cons |   .2016417   .0881346     2.29   0.022     .0286726    .3746109\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_deathp female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       926\n-------------+----------------------------------   F(5, 920)       =      1.67\n       Model |  3.35214734         5  .670429467   Prob > F        =    0.1387\n    Residual |  368.891467       920  .400968986   R-squared       =    0.0090\n-------------+----------------------------------   Adj R-squared   =    0.0036\n       Total |  372.243614       925  .402425529   Root MSE        =    .63322\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n   wp_deathp |   .0796663   .0474724     1.68   0.094    -.0135005    .1728331\n      female |  -.0278627   .0420944    -0.66   0.508    -.1104749    .0547495\n         age |  -.0028224   .0017314    -1.63   0.103    -.0062204    .0005756\n      income |   .0996175   .0892251     1.12   0.265    -.0754907    .2747258\n  university |  -.0545487   .0444678    -1.23   0.220    -.1418189    .0327214\n       _cons |   .1258034   .0889922     1.41   0.158    -.0488478    .3004546\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_gaymarriage female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       925\n-------------+----------------------------------   F(5, 919)       =      1.13\n       Model |  2.26814942         5  .453629885   Prob > F        =    0.3428\n    Residual |   369.02527       919  .401550892   R-squared       =    0.0061\n-------------+----------------------------------   Adj R-squared   =    0.0007\n       Total |  371.293419       924  .401832705   Root MSE        =    .63368\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_gaymarr~e |  -.0049728   .0494871    -0.10   0.920    -.1020937    .0921481\n      female |  -.0247821   .0422338    -0.59   0.557    -.1076679    .0581038\n         age |  -.0031186   .0017287    -1.80   0.072    -.0065113    .0002742\n      income |   .0874685   .0892838     0.98   0.328    -.0877554    .2626924\n  university |  -.0602069   .0446771    -1.35   0.178    -.1478879    .0274742\n       _cons |   .1761676   .0865548     2.04   0.042     .0062996    .3460356\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_guncontrol female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       927\n-------------+----------------------------------   F(5, 921)       =      1.16\n       Model |  2.32188711         5  .464377423   Prob > F        =    0.3290\n    Residual |  369.928455       921   .40165956   R-squared       =    0.0062\n-------------+----------------------------------   Adj R-squared   =    0.0008\n       Total |  372.250342       926  .401998209   Root MSE        =    .63377\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_guncont~l |   .0330061   .0632534     0.52   0.602    -.0911314    .1571436\n      female |   -.025081   .0421359    -0.60   0.552    -.1077746    .0576126\n         age |  -.0030578   .0017265    -1.77   0.077    -.0064462    .0003305\n      income |   .0821513   .0885553     0.93   0.354    -.0916424    .2559449\n  university |   -.059808   .0443209    -1.35   0.178    -.1467896    .0271736\n       _cons |   .1697745   .0848364     2.00   0.046     .0032795    .3362695\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_immigration female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       919\n-------------+----------------------------------   F(5, 913)       =      1.49\n       Model |  2.99862732         5  .599725465   Prob > F        =    0.1908\n    Residual |  367.742027       913  .402784258   R-squared       =    0.0081\n-------------+----------------------------------   Adj R-squared   =    0.0027\n       Total |  370.740655       918  .403856922   Root MSE        =    .63465\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_immigra~n |   .0781715    .052567     1.49   0.137    -.0249947    .1813377\n      female |   -.018295   .0423973    -0.43   0.666    -.1015026    .0649126\n         age |  -.0030497   .0017322    -1.76   0.079    -.0064493    .0003499\n      income |   .0927517   .0893628     1.04   0.300    -.0826285     .268132\n  university |  -.0596839   .0446357    -1.34   0.182    -.1472844    .0279166\n       _cons |    .141495   .0866173     1.63   0.103     -.028497    .3114871\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_milspend female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       870\n-------------+----------------------------------   F(5, 864)       =      1.28\n       Model |  2.58845606         5  .517691213   Prob > F        =    0.2709\n    Residual |  349.822015       864  .404886592   R-squared       =    0.0073\n-------------+----------------------------------   Adj R-squared   =    0.0016\n       Total |  352.410471       869   .40553564   Root MSE        =    .63631\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n wp_milspend |   .0004983   .0496102     0.01   0.992    -.0968722    .0978689\n      female |  -.0486619   .0437016    -1.11   0.266    -.1344357    .0371119\n         age |  -.0030825   .0017435    -1.77   0.077    -.0065045    .0003395\n      income |   .0941649   .0913333     1.03   0.303    -.0850962     .273426\n  university |  -.0628112   .0457349    -1.37   0.170    -.1525757    .0269533\n       _cons |   .1817194    .089807     2.02   0.043     .0054539    .3579849\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_obedience female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       926\n-------------+----------------------------------   F(5, 920)       =      1.09\n       Model |  2.18991158         5  .437982316   Prob > F        =    0.3622\n    Residual |  368.420554       920  .400457124   R-squared       =    0.0059\n-------------+----------------------------------   Adj R-squared   =    0.0005\n       Total |  370.610466       925  .400659963   Root MSE        =    .63282\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_obedience |   .0049176   .0506241     0.10   0.923    -.0944345    .1042696\n      female |  -.0301084    .042078    -0.72   0.474    -.1126883    .0524715\n         age |  -.0031424   .0017259    -1.82   0.069    -.0065296    .0002447\n      income |   .0718968   .0885537     0.81   0.417    -.1018938    .2456874\n  university |  -.0585365   .0446278    -1.31   0.190    -.1461207    .0290477\n       _cons |   .1825114    .088181     2.07   0.039     .0094521    .3555707\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_patriotism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       926\n-------------+----------------------------------   F(5, 920)       =      2.17\n       Model |  4.33346627         5  .866693255   Prob > F        =    0.0557\n    Residual |  367.858326       920  .399846007   R-squared       =    0.0116\n-------------+----------------------------------   Adj R-squared   =    0.0063\n       Total |  372.191793       925  .402369506   Root MSE        =    .63233\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_patriot~m |   .1229144   .0523242     2.35   0.019     .0202258     .225603\n      female |    -.02639   .0420281    -0.63   0.530    -.1088721    .0560921\n         age |  -.0028238   .0017246    -1.64   0.102    -.0062084    .0005608\n      income |   .0825506   .0884063     0.93   0.351    -.0909508     .256052\n  university |  -.0568498   .0442149    -1.29   0.199    -.1436235     .029924\n       _cons |   .0792248   .0926701     0.85   0.393    -.1026445    .2610941\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_pollution female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       927\n-------------+----------------------------------   F(5, 921)       =      1.08\n       Model |  2.17618409         5  .435236818   Prob > F        =    0.3679\n    Residual |  369.963237       921  .401697326   R-squared       =    0.0058\n-------------+----------------------------------   Adj R-squared   =    0.0005\n       Total |  372.139421       926  .401878425   Root MSE        =     .6338\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_pollution |  -.0189365   .0812478    -0.23   0.816    -.1783889    .1405159\n      female |  -.0252852   .0421143    -0.60   0.548    -.1079362    .0573659\n         age |  -.0030541   .0017273    -1.77   0.077     -.006444    .0003359\n      income |   .0798742   .0884837     0.90   0.367    -.0937789    .2535273\n  university |  -.0595172   .0443107    -1.34   0.180    -.1464788    .0274444\n       _cons |    .176897   .0845143     2.09   0.037     .0110341    .3427599\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_socialism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       923\n-------------+----------------------------------   F(5, 917)       =      1.09\n       Model |  2.19218236         5  .438436472   Prob > F        =    0.3653\n    Residual |  369.498268       917  .402942495   R-squared       =    0.0059\n-------------+----------------------------------   Adj R-squared   =    0.0005\n       Total |   371.69045       922  .403134979   Root MSE        =    .63478\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_socialism |   .0182944   .0511999     0.36   0.721    -.0821883    .1187771\n      female |  -.0240771   .0423663    -0.57   0.570    -.1072231     .059069\n         age |  -.0030439    .001731    -1.76   0.079     -.006441    .0003532\n      income |   .0816932   .0888926     0.92   0.358    -.0927633    .2561497\n  university |   -.058738   .0445392    -1.32   0.188    -.1461486    .0286726\n       _cons |   .1657011   .0863104     1.92   0.055    -.0036878      .33509\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_taxcuts female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       921\n-------------+----------------------------------   F(5, 915)       =      1.11\n       Model |  2.21724982         5  .443449964   Prob > F        =    0.3526\n    Residual |  365.108831       915  .399026044   R-squared       =    0.0060\n-------------+----------------------------------   Adj R-squared   =    0.0006\n       Total |   367.32608       920  .399267479   Root MSE        =    .63169\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n  wp_taxcuts |   .0142807   .0500518     0.29   0.775     -.083949    .1125104\n      female |  -.0248354    .042093    -0.59   0.555    -.1074455    .0577747\n         age |  -.0031243   .0017273    -1.81   0.071    -.0065143    .0002657\n      income |   .0868977   .0885271     0.98   0.327    -.0868421    .2606375\n  university |  -.0553634   .0442648    -1.25   0.211    -.1422357    .0315089\n       _cons |   .1653938   .0911694     1.81   0.070    -.0135317    .3443192\n------------------------------------------------------------------------------\n. regress mean_dif2 wp_women female age income university \n\n      Source |       SS           df       MS      Number of obs   =       926\n-------------+----------------------------------   F(5, 920)       =      1.37\n       Model |  2.75063385         5  .550126769   Prob > F        =    0.2327\n    Residual |  369.089887       920   .40118466   R-squared       =    0.0074\n-------------+----------------------------------   Adj R-squared   =    0.0020\n       Total |  371.840521       925  .401989753   Root MSE        =    .63339\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n    wp_women |    .102437   .0900127     1.14   0.255    -.0742171    .2790911\n      female |  -.0202705   .0422945    -0.48   0.632    -.1032753    .0627343\n         age |  -.0032274   .0017266    -1.87   0.062    -.0066159    .0001611\n      income |   .0809298    .088928     0.91   0.363    -.0935955     .255455\n  university |  -.0593109   .0443245    -1.34   0.181    -.1462997    .0276779\n       _cons |   .1704788   .0846558     2.01   0.044     .0043379    .3366196\n------------------------------------------------------------------------------\n.   \n. regress mean_ph_dif3_all wp_right2 female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       795\n-------------+----------------------------------   F(5, 789)       =      1.40\n       Model |  .461488476         5  .092297695   Prob > F        =    0.2215\n    Residual |  51.9688475       789  .065866727   R-squared       =    0.0088\n-------------+----------------------------------   Adj R-squared   =    0.0025\n       Total |  52.4303359       794  .066033169   Root MSE        =    .25665\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n   wp_right2 |  -.0741532    .041523    -1.79   0.075    -.1556618    .0073554\n      female |   .0265993   .0183138     1.45   0.147    -.0093502    .0625487\n         age |  -.0005056   .0007245    -0.70   0.485    -.0019279    .0009166\n      income |  -.0090882   .0388963    -0.23   0.815    -.0854408    .0672644\n  university |   .0100965   .0191123     0.53   0.597    -.0274204    .0476134\n       _cons |   .0677992    .040596     1.67   0.095    -.0118897     .147488\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_abortion female age income university   \n\n      Source |       SS           df       MS      Number of obs   =       790\n-------------+----------------------------------   F(5, 784)       =      1.06\n       Model |  .352697159         5  .070539432   Prob > F        =    0.3797\n    Residual |   52.042024       784  .066380133   R-squared       =    0.0067\n-------------+----------------------------------   Adj R-squared   =    0.0004\n       Total |  52.3947212       789  .066406491   Root MSE        =    .25764\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n wp_abortion |  -.0274342   .0214302    -1.28   0.201    -.0695016    .0146332\n      female |   .0273894   .0184392     1.49   0.138    -.0088067    .0635854\n         age |  -.0005564   .0007281    -0.76   0.445    -.0019857    .0008728\n      income |   -.009546   .0391664    -0.24   0.808    -.0864295    .0673375\n  university |   .0112476   .0192385     0.58   0.559    -.0265175    .0490127\n       _cons |   .0479071   .0375749     1.27   0.203    -.0258522    .1216665\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_capitalism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       787\n-------------+----------------------------------   F(5, 781)       =      0.76\n       Model |  .252774441         5  .050554888   Prob > F        =    0.5797\n    Residual |  52.0362687       781  .066627745   R-squared       =    0.0048\n-------------+----------------------------------   Adj R-squared   =   -0.0015\n       Total |  52.2890431       786    .0665255   Root MSE        =    .25812\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_capital~m |  -.0049791   .0226977    -0.22   0.826    -.0495347    .0395766\n      female |   .0272207   .0185754     1.47   0.143    -.0092429    .0636842\n         age |  -.0006051   .0007287    -0.83   0.407    -.0020354    .0008253\n      income |  -.0036283   .0399677    -0.09   0.928    -.0820853    .0748286\n  university |    .012348   .0192586     0.64   0.522    -.0254567    .0501527\n       _cons |    .038847   .0373981     1.04   0.299    -.0345657    .1122597\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_cencorship female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       785\n-------------+----------------------------------   F(5, 779)       =      2.86\n       Model |  .942526649         5   .18850533   Prob > F        =    0.0145\n    Residual |  51.4223402       779  .066010706   R-squared       =    0.0180\n-------------+----------------------------------   Adj R-squared   =    0.0117\n       Total |  52.3648668       784  .066791922   Root MSE        =    .25693\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_cencors~p |  -.0700174   .0216417    -3.24   0.001    -.1125002   -.0275345\n      female |   .0313801   .0184859     1.70   0.090     -.004908    .0676681\n         age |  -.0007929   .0007294    -1.09   0.277    -.0022248    .0006389\n      income |  -.0244134   .0394664    -0.62   0.536    -.1018865    .0530597\n  university |   .0101411   .0192315     0.53   0.598    -.0276106    .0478928\n       _cons |   .0772322   .0384377     2.01   0.045     .0017785    .1526859\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_deathp female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       788\n-------------+----------------------------------   F(5, 782)       =      0.99\n       Model |   .33018586         5  .066037172   Prob > F        =    0.4214\n    Residual |  52.0474156       782  .066556797   R-squared       =    0.0063\n-------------+----------------------------------   Adj R-squared   =   -0.0000\n       Total |  52.3776014       787  .066553496   Root MSE        =    .25799\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n   wp_deathp |  -.0224191   .0210415    -1.07   0.287    -.0637237    .0188854\n      female |   .0281312   .0184938     1.52   0.129    -.0081722    .0644346\n         age |  -.0006475   .0007318    -0.88   0.377     -.002084     .000789\n      income |  -.0120053   .0395501    -0.30   0.762    -.0896422    .0656315\n  university |   .0125064   .0192892     0.65   0.517    -.0253583     .050371\n       _cons |   .0501427   .0387033     1.30   0.196    -.0258319    .1261173\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_gaymarriage female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       787\n-------------+----------------------------------   F(5, 781)       =      1.27\n       Model |  .419178565         5  .083835713   Prob > F        =    0.2769\n    Residual |  51.7477981       781  .066258384   R-squared       =    0.0080\n-------------+----------------------------------   Adj R-squared   =    0.0017\n       Total |  52.1669766       786  .066370199   Root MSE        =    .25741\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_gaymarr~e |  -.0312377   .0213298    -1.46   0.143    -.0731082    .0106327\n      female |   .0269048   .0184845     1.46   0.146    -.0093804      .06319\n         age |  -.0005614   .0007288    -0.77   0.441    -.0019919    .0008692\n      income |  -.0107495   .0394813    -0.27   0.785    -.0882515    .0667526\n  university |   .0114576   .0193406     0.59   0.554    -.0265082    .0494233\n       _cons |   .0496638   .0376607     1.32   0.188    -.0242644     .123592\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_guncontrol female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       789\n-------------+----------------------------------   F(5, 783)       =      0.74\n       Model |  .247487414         5  .049497483   Prob > F        =    0.5912\n    Residual |  52.1471773       783  .066599205   R-squared       =    0.0047\n-------------+----------------------------------   Adj R-squared   =   -0.0016\n       Total |  52.3946647       788  .066490691   Root MSE        =    .25807\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_guncont~l |   .0053669   .0280652     0.19   0.848    -.0497251    .0604588\n      female |   .0271983   .0184929     1.47   0.142    -.0091032    .0634999\n         age |  -.0005667   .0007295    -0.78   0.438    -.0019986    .0008653\n      income |  -.0044872   .0391158    -0.11   0.909    -.0812716    .0722971\n  university |   .0138317   .0192277     0.72   0.472    -.0239123    .0515757\n       _cons |   .0341116   .0367757     0.93   0.354     -.038079    .1063023\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_immigration female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       781\n-------------+----------------------------------   F(5, 775)       =      0.77\n       Model |   .25918723         5  .051837446   Prob > F        =    0.5705\n    Residual |  52.0819213       775  .067202479   R-squared       =    0.0050\n-------------+----------------------------------   Adj R-squared   =   -0.0015\n       Total |  52.3411085       780  .067103985   Root MSE        =    .25923\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_immigra~n |  -.0064311   .0235032    -0.27   0.784    -.0525686    .0397064\n      female |   .0274723   .0186739     1.47   0.142    -.0091851    .0641297\n         age |  -.0005844   .0007345    -0.80   0.426    -.0020263    .0008574\n      income |  -.0066955    .039718    -0.17   0.866    -.0846632    .0712722\n  university |   .0140787   .0194351     0.72   0.469     -.024073    .0522304\n       _cons |   .0385701   .0376604     1.02   0.306    -.0353584    .1124987\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_milspend female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       733\n-------------+----------------------------------   F(5, 727)       =      1.16\n       Model |  .376781408         5  .075356282   Prob > F        =    0.3267\n    Residual |   47.178777       727  .064895154   R-squared       =    0.0079\n-------------+----------------------------------   Adj R-squared   =    0.0011\n       Total |  47.5555584       732   .06496661   Root MSE        =    .25475\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n wp_milspend |  -.0292702   .0215725    -1.36   0.175     -.071622    .0130817\n      female |   .0240563   .0189447     1.27   0.205    -.0131365    .0612492\n         age |  -.0006531   .0007256    -0.90   0.368    -.0020776    .0007713\n      income |   -.004753   .0397249    -0.12   0.905    -.0827422    .0732361\n  university |   .0157217   .0195339     0.80   0.421    -.0226278    .0540712\n       _cons |   .0534543   .0386881     1.38   0.167    -.0224995    .1294081\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_obedience female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       788\n-------------+----------------------------------   F(5, 782)       =      0.88\n       Model |  .291815772         5  .058363154   Prob > F        =    0.4958\n    Residual |  52.0293691       782   .06653372   R-squared       =    0.0056\n-------------+----------------------------------   Adj R-squared   =   -0.0008\n       Total |  52.3211849       787  .066481811   Root MSE        =    .25794\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_obedience |  -.0194714   .0224512    -0.87   0.386     -.063543    .0246003\n      female |   .0284451   .0185099     1.54   0.125      -.00789    .0647801\n         age |  -.0004972   .0007308    -0.68   0.496    -.0019318    .0009374\n      income |  -.0033529   .0391639    -0.09   0.932    -.0802318     .073526\n  university |   .0104501   .0193935     0.54   0.590    -.0276193    .0485195\n       _cons |   .0440785    .038413     1.15   0.252    -.0313262    .1194833\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_patriotism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       788\n-------------+----------------------------------   F(5, 782)       =      0.97\n       Model |  .321498422         5  .064299684   Prob > F        =    0.4354\n    Residual |  51.8567356       782  .066312961   R-squared       =    0.0062\n-------------+----------------------------------   Adj R-squared   =   -0.0002\n       Total |   52.178234       787   .06630017   Root MSE        =    .25751\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_patriot~m |  -.0212288   .0230688    -0.92   0.358     -.066513    .0240554\n      female |   .0286829   .0184536     1.55   0.121    -.0075416    .0649074\n         age |  -.0006301   .0007289    -0.86   0.388    -.0020608    .0008007\n      income |  -.0097029    .039073    -0.25   0.804    -.0864033    .0669976\n  university |    .011572   .0191771     0.60   0.546    -.0260726    .0492166\n       _cons |   .0552679   .0406494     1.36   0.174    -.0245269    .1350628\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_pollution female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       789\n-------------+----------------------------------   F(5, 783)       =      0.97\n       Model |  .320618384         5  .064123677   Prob > F        =    0.4382\n    Residual |  52.0184621       783  .066434817   R-squared       =    0.0061\n-------------+----------------------------------   Adj R-squared   =   -0.0002\n       Total |  52.3390805       788  .066420153   Root MSE        =    .25775\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_pollution |   .0357278   .0350534     1.02   0.308    -.0330819    .1045375\n      female |   .0275031   .0184587     1.49   0.137    -.0087312    .0637374\n         age |    -.00055    .000729    -0.75   0.451    -.0019811    .0008811\n      income |  -.0012303   .0390627    -0.03   0.975    -.0779104    .0754497\n  university |   .0150146   .0191939     0.78   0.434     -.022663    .0526923\n       _cons |   .0281056    .036632     0.77   0.443    -.0438031    .1000142\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_socialism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       785\n-------------+----------------------------------   F(5, 779)       =      1.29\n       Model |  .429003548         5   .08580071   Prob > F        =    0.2666\n    Residual |  51.8590442       779  .066571302   R-squared       =    0.0082\n-------------+----------------------------------   Adj R-squared   =    0.0018\n       Total |  52.2880477       784  .066693938   Root MSE        =    .25801\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_socialism |   .0370367   .0225457     1.64   0.101    -.0072208    .0812942\n      female |   .0299288   .0185707     1.61   0.107    -.0065257    .0663833\n         age |  -.0006021     .00073    -0.82   0.410     -.002035    .0008309\n      income |  -.0074319   .0391586    -0.19   0.850    -.0843008    .0694371\n  university |   .0110792   .0192835     0.57   0.566    -.0267746    .0489331\n       _cons |    .023354   .0372186     0.63   0.531    -.0497066    .0964145\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_taxcuts female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       785\n-------------+----------------------------------   F(5, 779)       =      1.85\n       Model |  .603453671         5  .120690734   Prob > F        =    0.1011\n    Residual |  50.8554685       779  .065283015   R-squared       =    0.0117\n-------------+----------------------------------   Adj R-squared   =    0.0054\n       Total |  51.4589221       784   .06563638   Root MSE        =    .25551\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n  wp_taxcuts |   -.050794   .0218547    -2.32   0.020     -.093695    -.007893\n      female |   .0251069   .0183435     1.37   0.171    -.0109016    .0611154\n         age |   -.000808    .000726    -1.11   0.266    -.0022331    .0006172\n      income |  -.0014091   .0388421    -0.04   0.971    -.0776567    .0748384\n  university |   .0163039   .0190438     0.86   0.392    -.0210793    .0536871\n       _cons |   .0746042   .0395512     1.89   0.060    -.0030354    .1522438\n------------------------------------------------------------------------------\n. regress mean_ph_dif3_all wp_women female age income university \n\n      Source |       SS           df       MS      Number of obs   =       789\n-------------+----------------------------------   F(5, 783)       =      0.77\n       Model |  .255365624         5  .051073125   Prob > F        =    0.5737\n    Residual |  52.1347449       783  .066583327   R-squared       =    0.0049\n-------------+----------------------------------   Adj R-squared   =   -0.0015\n       Total |  52.3901106       788  .066484912   Root MSE        =    .25804\n\n------------------------------------------------------------------------------\nmean_p~3_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n    wp_women |  -.0159998    .037674    -0.42   0.671    -.0899539    .0579542\n      female |   .0261525   .0185626     1.41   0.159    -.0102859    .0625908\n         age |  -.0005576   .0007296    -0.76   0.445    -.0019899    .0008747\n      income |  -.0052771   .0393065    -0.13   0.893    -.0824358    .0718816\n  university |   .0132449   .0192326     0.69   0.491    -.0245087    .0509986\n       _cons |   .0372489   .0367274     1.01   0.311    -.0348469    .1093446\n------------------------------------------------------------------------------\n.     \n. regress mean_ph_dif2_all wp_right2 female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       796\n-------------+----------------------------------   F(5, 790)       =      1.87\n       Model |  .631060926         5  .126212185   Prob > F        =    0.0971\n    Residual |  53.3020628       790  .067470966   R-squared       =    0.0117\n-------------+----------------------------------   Adj R-squared   =    0.0054\n       Total |  53.9331237       795  .067840407   Root MSE        =    .25975\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n   wp_right2 |  -.0531159   .0421163    -1.26   0.208    -.1357891    .0295573\n      female |   .0417556   .0185246     2.25   0.024     .0053924    .0781189\n         age |  -.0004022   .0007328    -0.55   0.583    -.0018406    .0010362\n      income |  -.0588729   .0393908    -1.49   0.135    -.1361959    .0184501\n  university |  -.0036823   .0193342    -0.19   0.849    -.0416349    .0342703\n       _cons |   .0772974   .0411082     1.88   0.060    -.0033968    .1579916\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_abortion female age income university   \n\n      Source |       SS           df       MS      Number of obs   =       791\n-------------+----------------------------------   F(5, 785)       =      1.64\n       Model |  .556306414         5  .111261283   Prob > F        =    0.1477\n    Residual |  53.3472081       785  .067958227   R-squared       =    0.0103\n-------------+----------------------------------   Adj R-squared   =    0.0040\n       Total |  53.9035145       790  .068232297   Root MSE        =    .26069\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n wp_abortion |   -.015364   .0217024    -0.71   0.479    -.0579656    .0272376\n      female |   .0426767   .0186467     2.29   0.022     .0060734      .07928\n         age |  -.0004301   .0007362    -0.58   0.559    -.0018753    .0010151\n      income |   -.058121   .0396559    -1.47   0.143    -.1359651    .0197232\n  university |  -.0017518   .0194553    -0.09   0.928    -.0399423    .0364387\n       _cons |    .059711   .0379948     1.57   0.116    -.0148723    .1342944\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_capitalism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       788\n-------------+----------------------------------   F(5, 782)       =      1.60\n       Model |  .546622987         5  .109324597   Prob > F        =    0.1568\n    Residual |  53.3288443       782  .068195453   R-squared       =    0.0101\n-------------+----------------------------------   Adj R-squared   =    0.0038\n       Total |  53.8754673       787  .068456756   Root MSE        =    .26114\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_capital~m |   .0136083   .0229182     0.59   0.553    -.0313802    .0585968\n      female |   .0428814   .0187795     2.28   0.023     .0060172    .0797457\n         age |  -.0004524   .0007367    -0.61   0.539    -.0018986    .0009938\n      income |   -.061271   .0404117    -1.52   0.130    -.1405993    .0180572\n  university |  -.0014578   .0194752    -0.07   0.940    -.0396877    .0367722\n       _cons |   .0498354    .037848     1.32   0.188    -.0244604    .1241312\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_cencorship female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       786\n-------------+----------------------------------   F(5, 780)       =      1.87\n       Model |  .636103885         5  .127220777   Prob > F        =    0.0978\n    Residual |  53.1506995       780  .068141922   R-squared       =    0.0118\n-------------+----------------------------------   Adj R-squared   =    0.0055\n       Total |  53.7868034       785  .068518221   Root MSE        =    .26104\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_cencors~p |  -.0316561   .0219991    -1.44   0.151    -.0748405    .0115283\n      female |   .0436812   .0187677     2.33   0.020       .00684    .0805224\n         age |  -.0005252   .0007407    -0.71   0.479    -.0019791    .0009288\n      income |  -.0604614   .0401079    -1.51   0.132    -.1391936    .0182707\n  university |  -.0026489   .0195281    -0.14   0.892    -.0409827    .0356849\n       _cons |   .0698827   .0390011     1.79   0.074    -.0066768    .1464422\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_deathp female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       789\n-------------+----------------------------------   F(5, 783)       =      1.59\n       Model |  .541442258         5  .108288452   Prob > F        =    0.1602\n    Residual |  53.3062697       783  .068079527   R-squared       =    0.0101\n-------------+----------------------------------   Adj R-squared   =    0.0037\n       Total |   53.847712       788   .06833466   Root MSE        =    .26092\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n   wp_deathp |  -.0167181   .0212759    -0.79   0.432    -.0584826    .0250465\n      female |   .0424557    .018691     2.27   0.023     .0057653     .079146\n         age |   -.000469   .0007396    -0.63   0.526    -.0019209    .0009829\n      income |  -.0573315   .0400076    -1.43   0.152    -.1358664    .0212034\n  university |  -.0023309   .0194976    -0.12   0.905    -.0406047    .0359429\n       _cons |   .0625196   .0390842     1.60   0.110    -.0142027    .1392419\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_gaymarriage female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       788\n-------------+----------------------------------   F(5, 782)       =      1.88\n       Model |  .636594435         5  .127318887   Prob > F        =    0.0952\n    Residual |  52.9138967       782   .06766483   R-squared       =    0.0119\n-------------+----------------------------------   Adj R-squared   =    0.0056\n       Total |  53.5504911       787  .068043826   Root MSE        =    .26012\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_gaymarr~e |  -.0294067   .0215678    -1.36   0.173    -.0717443    .0129308\n      female |   .0416635   .0186696     2.23   0.026     .0050151    .0783119\n         age |  -.0004074    .000736    -0.55   0.580    -.0018522    .0010374\n      income |  -.0565654   .0399058    -1.42   0.157    -.1349006    .0217698\n  university |  -.0034059   .0195273    -0.17   0.862    -.0417381    .0349264\n       _cons |    .064564   .0380037     1.70   0.090    -.0100373    .1391653\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_guncontrol female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       790\n-------------+----------------------------------   F(5, 784)       =      1.76\n       Model |  .598561437         5  .119712287   Prob > F        =    0.1185\n    Residual |  53.3032285       784  .067988812   R-squared       =    0.0111\n-------------+----------------------------------   Adj R-squared   =    0.0048\n       Total |  53.9017899       789   .06831659   Root MSE        =    .26075\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_guncont~l |  -.0305017   .0284785    -1.07   0.284    -.0864049    .0254015\n      female |      .0417    .018671     2.23   0.026      .005049     .078351\n         age |   -.000458   .0007366    -0.62   0.534     -.001904     .000988\n      income |  -.0561215   .0395388    -1.42   0.156     -.133736     .021493\n  university |  -.0014944    .019424    -0.08   0.939    -.0396235    .0366348\n       _cons |   .0591168   .0371452     1.59   0.112    -.0137989    .1320326\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_immigration female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       782\n-------------+----------------------------------   F(5, 776)       =      1.43\n       Model |  .489531034         5  .097906207   Prob > F        =    0.2126\n    Residual |  53.2910221       776  .068673998   R-squared       =    0.0091\n-------------+----------------------------------   Adj R-squared   =    0.0027\n       Total |  53.7805531       781  .068861144   Root MSE        =    .26206\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_immigra~n |  -.0008105   .0237128    -0.03   0.973    -.0473593    .0457384\n      female |   .0417486   .0188623     2.21   0.027     .0047213    .0787759\n         age |  -.0004077   .0007421    -0.55   0.583    -.0018644    .0010489\n      income |  -.0528861    .040153    -1.32   0.188    -.1317074    .0259353\n  university |  -.0010141   .0196418    -0.05   0.959    -.0395715    .0375432\n       _cons |   .0518713   .0379945     1.37   0.173    -.0227129    .1264555\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_milspend female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       734\n-------------+----------------------------------   F(5, 728)       =      1.21\n       Model |  .395024937         5  .079004987   Prob > F        =    0.3015\n    Residual |  47.4409971       728  .065166205   R-squared       =    0.0083\n-------------+----------------------------------   Adj R-squared   =    0.0014\n       Total |   47.836022       733  .065260603   Root MSE        =    .25528\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n wp_milspend |  -.0119269   .0216118    -0.55   0.581    -.0543558    .0305019\n      female |   .0337258   .0189707     1.78   0.076     -.003518    .0709696\n         age |  -.0005291   .0007266    -0.73   0.467    -.0019556    .0008974\n      income |  -.0520886   .0398206    -1.31   0.191    -.1302655    .0260882\n  university |  -.0060779   .0195623    -0.31   0.756    -.0444831    .0323273\n       _cons |   .0684259   .0387381     1.77   0.078    -.0076257    .1444776\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_obedience female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       789\n-------------+----------------------------------   F(5, 783)       =      1.64\n       Model |  .557661539         5  .111532308   Prob > F        =    0.1476\n    Residual |  53.3362121       783  .068117768   R-squared       =    0.0103\n-------------+----------------------------------   Adj R-squared   =    0.0040\n       Total |  53.8938737       788  .068393241   Root MSE        =    .26099\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_obedience |  -.0152776   .0226769    -0.67   0.501    -.0597923     .029237\n      female |   .0436527   .0187165     2.33   0.020     .0069123    .0803931\n         age |  -.0004026   .0007392    -0.54   0.586    -.0018537    .0010484\n      income |  -.0543833   .0396375    -1.37   0.170    -.1321916     .023425\n  university |  -.0024141   .0196021    -0.12   0.902    -.0408929    .0360647\n       _cons |    .060264   .0387522     1.56   0.120    -.0158065    .1363344\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_patriotism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       789\n-------------+----------------------------------   F(5, 783)       =      1.64\n       Model |  .558441319         5  .111688264   Prob > F        =    0.1464\n    Residual |   53.254015       783   .06801279   R-squared       =    0.0104\n-------------+----------------------------------   Adj R-squared   =    0.0041\n       Total |  53.8124563       788  .068289919   Root MSE        =    .26079\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_patriot~m |   .0008803   .0232879     0.04   0.970    -.0448338    .0465944\n      female |   .0434073   .0186779     2.32   0.020     .0067426    .0800721\n         age |  -.0004447   .0007377    -0.60   0.547    -.0018928    .0010035\n      income |  -.0594799   .0395889    -1.50   0.133    -.1371928     .018233\n  university |  -.0015349   .0194154    -0.08   0.937    -.0396473    .0365775\n       _cons |   .0551897   .0411288     1.34   0.180    -.0255461    .1359255\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_pollution female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       790\n-------------+----------------------------------   F(5, 784)       =      1.53\n       Model |  .521378521         5  .104275704   Prob > F        =    0.1775\n    Residual |  53.3805452       784   .06808743   R-squared       =    0.0097\n-------------+----------------------------------   Adj R-squared   =    0.0034\n       Total |  53.9019238       789   .06831676   Root MSE        =    .26094\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_pollution |   .0005518   .0354859     0.02   0.988    -.0691068    .0702105\n      female |    .042331   .0186752     2.27   0.024     .0056716    .0789903\n         age |  -.0004395   .0007376    -0.60   0.551    -.0018874    .0010084\n      income |  -.0550388   .0395602    -1.39   0.165    -.1326951    .0226176\n  university |  -.0005929   .0194252    -0.03   0.976    -.0387244    .0375386\n       _cons |   .0527284   .0370501     1.42   0.155    -.0200008    .1254576\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_socialism female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       786\n-------------+----------------------------------   F(5, 780)       =      1.80\n       Model |  .612855747         5  .122571149   Prob > F        =    0.1113\n    Residual |  53.2475868       780  .068266137   R-squared       =    0.0114\n-------------+----------------------------------   Adj R-squared   =    0.0050\n       Total |  53.8604425       785  .068612029   Root MSE        =    .26128\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\nwp_socialism |  -.0273926   .0228201    -1.20   0.230    -.0721887    .0174035\n      female |   .0403175   .0187942     2.15   0.032     .0034244    .0772106\n         age |   -.000454   .0007387    -0.61   0.539    -.0019041    .0009962\n      income |  -.0532732   .0396608    -1.34   0.180    -.1311278    .0245814\n  university |  -.0002687   .0195164    -0.01   0.989    -.0385797    .0380422\n       _cons |   .0635406   .0376984     1.69   0.092    -.0104617    .1375429\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_taxcuts female age income university  \n\n      Source |       SS           df       MS      Number of obs   =       786\n-------------+----------------------------------   F(5, 780)       =      1.94\n       Model |  .659711326         5  .131942265   Prob > F        =    0.0856\n    Residual |  53.0577564       780  .068022765   R-squared       =    0.0123\n-------------+----------------------------------   Adj R-squared   =    0.0059\n       Total |  53.7174678       785  .068429895   Root MSE        =    .26081\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n  wp_taxcuts |  -.0294665   .0222994    -1.32   0.187    -.0732404    .0143073\n      female |   .0440057   .0187128     2.35   0.019     .0072723    .0807391\n         age |  -.0005342   .0007406    -0.72   0.471    -.0019881    .0009197\n      income |  -.0549325   .0396607    -1.39   0.166    -.1327868    .0229218\n  university |   .0004892   .0194326     0.03   0.980    -.0376573    .0386357\n       _cons |   .0737054   .0403231     1.83   0.068    -.0054493    .1528601\n------------------------------------------------------------------------------\n. regress mean_ph_dif2_all wp_women female age income university \n\n      Source |       SS           df       MS      Number of obs   =       790\n-------------+----------------------------------   F(5, 784)       =      1.65\n       Model |  .560102296         5  .112020459   Prob > F        =    0.1453\n    Residual |  53.3439947       784   .06804081   R-squared       =    0.0104\n-------------+----------------------------------   Adj R-squared   =    0.0041\n       Total |   53.904097       789  .068319515   Root MSE        =    .26085\n\n------------------------------------------------------------------------------\nmean_p~2_all |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n    wp_women |   .0288333   .0380835     0.76   0.449    -.0459245     .103591\n      female |   .0439023   .0187528     2.34   0.019     .0070907    .0807139\n         age |  -.0004559   .0007371    -0.62   0.536    -.0019029    .0009911\n      income |  -.0529817   .0397485    -1.33   0.183    -.1310078    .0250443\n  university |   .0003343   .0194353     0.02   0.986    -.0378171    .0384857\n       _cons |   .0485386   .0370904     1.31   0.191    -.0242697     .121347\n------------------------------------------------------------------------------\n.         \n.                              \n.   \n. * Table A8 Row 1\n. quietly regress mean_dif2 wp_right2 female age income university \n. estimates store A\n. quietly regress mean_dif2 wp_right2 female age income university if wp_right2\n> _ext==1\n. estimates store B\n. quietly regress mean_dif2 wp_right2 female age income university if political\n> _interest_dichox==1\n. estimates store C\n. esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                mean_dif2       mean_dif2       mean_dif2   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nwp_right2           0.104           0.206           0.323** \n                  (0.093)         (0.111)         (0.121)   \nfemale             -0.023          -0.050          -0.071   \n                  (0.042)         (0.060)         (0.060)   \nage                -0.003          -0.003          -0.002   \n                  (0.002)         (0.003)         (0.002)   \nincome              0.086           0.120           0.032   \n                  (0.088)         (0.122)         (0.125)   \nuniversity         -0.054          -0.021           0.003   \n                  (0.044)         (0.064)         (0.067)   \n_cons               0.131           0.033          -0.022   \n                  (0.093)         (0.128)         (0.130)   \n------------------------------------------------------------\nr2                  0.007           0.012           0.020   \nr2_a                0.002           0.002           0.009   \nN                 933.000         505.000         444.000   \n------------------------------------------------------------\n. regress mean_dif2 wp_right2 female age income university if political_interes\n> t_dichox==1, beta\n\n      Source |       SS           df       MS      Number of obs   =       444\n-------------+----------------------------------   F(5, 438)       =      1.78\n       Model |  3.33233263         5  .666466526   Prob > F        =    0.1162\n    Residual |  164.257414       438  .375016928   R-squared       =    0.0199\n-------------+----------------------------------   Adj R-squared   =    0.0087\n       Total |  167.589747       443  .378306427   Root MSE        =    .61239\n\n------------------------------------------------------------------------------\n   mean_dif2 |      Coef.   Std. Err.      t    P>|t|                     Beta\n-------------+----------------------------------------------------------------\n   wp_right2 |   .3233054    .121261     2.67   0.008                 .1276749\n      female |  -.0709586   .0596313    -1.19   0.235                -.0570675\n         age |  -.0015231   .0024292    -0.63   0.531                -.0301753\n      income |   .0323931   .1253699     0.26   0.796                 .0122521\n  university |   .0026998   .0667772     0.04   0.968                 .0019359\n       _cons |  -.0221748    .130452    -0.17   0.865                        .\n------------------------------------------------------------------------------\n. regress md2 wp2 female age income university if political_interest_dichox==1\n\n      Source |       SS           df       MS      Number of obs   =       444\n-------------+----------------------------------   F(5, 438)       =      1.78\n       Model |  8.34174647         5  1.66834929   Prob > F        =    0.1162\n    Residual |   411.18152       438  .938770593   R-squared       =    0.0199\n-------------+----------------------------------   Adj R-squared   =    0.0087\n       Total |  419.523266       443  .947005115   Root MSE        =     .9689\n\n------------------------------------------------------------------------------\n         md2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]\n-------------+----------------------------------------------------------------\n         wp2 |   .1154357    .043296     2.67   0.008     .0303419    .2005295\n      female |  -.1122688   .0943471    -1.19   0.235    -.2976982    .0731605\n         age |  -.0024098   .0038434    -0.63   0.531    -.0099636     .005144\n      income |   .0512515    .198357     0.26   0.796    -.3385983    .4411012\n  university |   .0042716   .1056531     0.04   0.968    -.2033785    .2119217\n       _cons |   .0404929   .1913442     0.21   0.832     -.335574    .4165599\n------------------------------------------------------------------------------\n. * Table A8 Row 4\n. quietly regress mean_ph_dif_all wp_right2 female age income university  \n. estimates store A\n. quietly regress mean_ph_dif_all wp_right2 female age income university if wp_\n> right2_ext==1\n. estimates store B\n. quietly regress mean_ph_dif_all wp_right2 female age income university if pol\n> itical_interest_dichox==1\n. estimates store C\n. esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n             mean_p~f_all    mean_p~f_all    mean_p~f_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nwp_right2          -0.069*         -0.053          -0.082   \n                  (0.034)         (0.040)         (0.045)   \nfemale              0.031*          0.071***        0.022   \n                  (0.015)         (0.021)         (0.022)   \nage                -0.000           0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.026          -0.014           0.010   \n                  (0.032)         (0.044)         (0.046)   \nuniversity          0.002          -0.001           0.002   \n                  (0.016)         (0.023)         (0.024)   \n_cons               0.073*          0.005           0.044   \n                  (0.033)         (0.046)         (0.047)   \n------------------------------------------------------------\nr2                  0.013           0.029           0.012   \nr2_a                0.007           0.018          -0.002   \nN                 806.000         432.000         377.000   \n------------------------------------------------------------\n.       \n.     \n"} -->
<pre><code>. *** Syntax for analyses of individual-level data
. *** Use data file 'Individual-data.dta' with this syntax
. * Figure 2
. ttest mean_neg2==mean_pos2 if wp_right2_dichox==0

Paired t test
------------------------------------------------------------------------------
Variable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
mean_n~2 |     471   -.0240817    .0228673    .4962785   -.0690165    .0208531
mean_p~2 |     471   -.0899855    .0252883    .5488198   -.1396775   -.0402934
---------+--------------------------------------------------------------------
    diff |     471    .0659037    .0320919    .6964764    .0028423    .1289652
------------------------------------------------------------------------------
     mean(diff) = mean(mean_neg2 - mean_pos2)                     t =   2.0536
 Ho: mean(diff) = 0                              degrees of freedom =      470

 Ha: mean(diff) &lt; 0           Ha: mean(diff) != 0           Ha: mean(diff) &gt; 0
 Pr(T &lt; t) = 0.9797         Pr(|T| &gt; |t|) = 0.0406          Pr(T &gt; t) = 0.0203
. ttest mean_neg2==mean_pos2 if wp_right2_dichox==1

Paired t test
------------------------------------------------------------------------------
Variable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
mean_n~2 |     463    .0213809    .0200558    .4315483   -.0180309    .0607927
mean_p~2 |     463   -.0680617    .0215774    .4642906   -.1104637   -.0256597
---------+--------------------------------------------------------------------
    diff |     463    .0894426    .0259995    .5594429    .0383506    .1405346
------------------------------------------------------------------------------
     mean(diff) = mean(mean_neg2 - mean_pos2)                     t =   3.4402
 Ho: mean(diff) = 0                              degrees of freedom =      462

 Ha: mean(diff) &lt; 0           Ha: mean(diff) != 0           Ha: mean(diff) &gt; 0
 Pr(T &lt; t) = 0.9997         Pr(|T| &gt; |t|) = 0.0006          Pr(T &gt; t) = 0.0003
. ttest mean_dif2, by(wp_right2_dichox)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     471    .0659037    .0320919    .6964764    .0028423    .1289652
       1 |     463    .0894426    .0259995    .5594429    .0383506    .1405346
---------+--------------------------------------------------------------------
combined |     934    .0775724     .020681    .6320417    .0369856    .1181591
---------+--------------------------------------------------------------------
    diff |           -.0235389    .0413786               -.1047449    .0576671
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -0.5689
Ho: diff = 0                                     degrees of freedom =      932

    Ha: diff &lt; 0                 Ha: diff != 0                 Ha: diff &gt; 0
 Pr(T &lt; t) = 0.2848         Pr(|T| &gt; |t|) = 0.5696          Pr(T &gt; t) = 0.7152
. * Table 2
. quietly regress mean_dif2 wp_right2 female age income university 
. estimates store A
. esttab A , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)

----------------------------
                      (1)   
                mean_dif2   
                     b/se   
----------------------------
wp_right2           0.104   
                  (0.093)   
female             -0.023   
                  (0.042)   
age                -0.003   
                  (0.002)   
income              0.086   
                  (0.088)   
university         -0.054   
                  (0.044)   
_cons               0.131   
                  (0.093)   
----------------------------
r2                  0.007   
r2_a                0.002   
N                 933.000   
----------------------------
. regress mean_dif2 wp_right2 female age income university, beta

      Source |       SS           df       MS      Number of obs   =       933
-------------+----------------------------------   F(5, 927)       =      1.34
       Model |   2.6843355         5    .5368671   Prob &gt; F        =    0.2430
    Residual |  370.026446       927  .399165529   R-squared       =    0.0072
-------------+----------------------------------   Adj R-squared   =    0.0018
       Total |  372.710781       932  .399904272   Root MSE        =     .6318

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|                     Beta
-------------+----------------------------------------------------------------
   wp_right2 |   .1035859    .093023     1.11   0.266                  .036934
      female |  -.0230074   .0418745    -0.55   0.583                -.0181692
         age |  -.0031561   .0017191    -1.84   0.067                 -.061052
      income |   .0856957   .0881939     0.97   0.331                 .0318768
  university |  -.0540114   .0442642    -1.22   0.223                -.0405662
       _cons |    .130539   .0926448     1.41   0.159                        .
------------------------------------------------------------------------------
. egen wp2 = std(wp_right2)
. egen md2 = std(mean_dif2)
. regress md2 wp2 female age income university

      Source |       SS           df       MS      Number of obs   =       933
-------------+----------------------------------   F(5, 927)       =      1.34
       Model |  6.71963057         5  1.34392611   Prob &gt; F        =    0.2430
    Residual |  926.278036       927  .999221182   R-squared       =    0.0072
-------------+----------------------------------   Adj R-squared   =    0.0018
       Total |  932.997666       932  1.00107046   Root MSE        =    .99961

------------------------------------------------------------------------------
         md2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         wp2 |   .0369852   .0332137     1.11   0.266    -.0281976    .1021679
      female |  -.0364017   .0662528    -0.55   0.583    -.1664246    .0936211
         age |  -.0049935   .0027199    -1.84   0.067    -.0103313    .0003443
      income |   .1355856    .139538     0.97   0.331    -.1382615    .4094327
  university |  -.0854555   .0700337    -1.22   0.223    -.2228985    .0519876
       _cons |   .1473403   .1319921     1.12   0.265    -.1116976    .4063783
------------------------------------------------------------------------------
. * Figure 6
. ttest mean_ph_neg_all==mean_ph_pos_all if wp_right2_dichox==0

Paired t test
------------------------------------------------------------------------------
Variable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
me~g_all |     411    .0275029     .007584     .153752    .0125945    .0424114
me~s_all |     411   -.0169125    .0071241     .144427   -.0309167   -.0029082
---------+--------------------------------------------------------------------
    diff |     411    .0444154    .0107432    .2177983    .0232968     .065534
------------------------------------------------------------------------------
     mean(diff) = mean(mean_ph_neg_all - mean_ph_pos_all)         t =   4.1343
 Ho: mean(diff) = 0                              degrees of freedom =      410

 Ha: mean(diff) &lt; 0           Ha: mean(diff) != 0           Ha: mean(diff) &gt; 0
 Pr(T &lt; t) = 1.0000         Pr(|T| &gt; |t|) = 0.0000          Pr(T &gt; t) = 0.0000
. ttest mean_ph_neg_all==mean_ph_pos_all if wp_right2_dichox==1

Paired t test
------------------------------------------------------------------------------
Variable |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
me~g_all |     396    .0074071    .0073337    .1459391   -.0070109    .0218251
me~s_all |     396   -.0162411    .0060894    .1211766   -.0282127   -.0042695
---------+--------------------------------------------------------------------
    diff |     396    .0236482     .010401    .2069764       .0032    .0440963
------------------------------------------------------------------------------
     mean(diff) = mean(mean_ph_neg_all - mean_ph_pos_all)         t =   2.2737
 Ho: mean(diff) = 0                              degrees of freedom =      395

 Ha: mean(diff) &lt; 0           Ha: mean(diff) != 0           Ha: mean(diff) &gt; 0
 Pr(T &lt; t) = 0.9882         Pr(|T| &gt; |t|) = 0.0235          Pr(T &gt; t) = 0.0118
. ttest mean_ph_dif_all, by(wp_right2_dichox)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     411    .0444154    .0107432    .2177983    .0232968     .065534
       1 |     396    .0236482     .010401    .2069764       .0032    .0440963
---------+--------------------------------------------------------------------
combined |     807    .0342248    .0074867     .212679    .0195291    .0489204
---------+--------------------------------------------------------------------
    diff |            .0207672    .0149673               -.0086124    .0501468
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   1.3875
Ho: diff = 0                                     degrees of freedom =      805

    Ha: diff &lt; 0                 Ha: diff != 0                 Ha: diff &gt; 0
 Pr(T &lt; t) = 0.9172         Pr(|T| &gt; |t|) = 0.1657          Pr(T &gt; t) = 0.0828
. * Table 5 Column 1
. quietly regress mean_ph_dif_all wp_right2 female age income university  
. estimates store A
. esttab A , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)

----------------------------
                      (1)   
             mean_p~f_all   
                     b/se   
----------------------------
wp_right2          -0.069*  
                  (0.034)   
female              0.031*  
                  (0.015)   
age                -0.000   
                  (0.001)   
income             -0.026   
                  (0.032)   
university          0.002   
                  (0.016)   
_cons               0.073*  
                  (0.033)   
----------------------------
r2                  0.013   
r2_a                0.007   
N                 806.000   
----------------------------
. regress mean_ph_dif_all wp_right2 female age income university, beta

      Source |       SS           df       MS      Number of obs   =       806
-------------+----------------------------------   F(5, 800)       =      2.06
       Model |  .464167318         5  .092833464   Prob &gt; F        =    0.0679
    Residual |  35.9916953       800  .044989619   R-squared       =    0.0127
-------------+----------------------------------   Adj R-squared   =    0.0066
       Total |  36.4558626       805  .045286786   Root MSE        =    .21211

------------------------------------------------------------------------------
mean_p~f_all |      Coef.   Std. Err.      t    P&gt;|t|                     Beta
-------------+----------------------------------------------------------------
   wp_right2 |   -.069114   .0340791    -2.03   0.043                -.0720893
      female |    .030908   .0150366     2.06   0.040                 .0726639
         age |  -.0004451   .0005922    -0.75   0.452                -.0266983
      income |  -.0256898   .0320628    -0.80   0.423                -.0282353
  university |   .0017661   .0156791     0.11   0.910                  .004003
       _cons |    .072752   .0333775     2.18   0.030                        .
------------------------------------------------------------------------------
. egen mp2 = std(mean_ph_dif_all)
(127 missing values generated)
. regress mp2 wp2 female age income university 

      Source |       SS           df       MS      Number of obs   =       806
-------------+----------------------------------   F(5, 800)       =      2.06
       Model |  10.2618427         5  2.05236853   Prob &gt; F        =    0.0679
    Residual |  795.706839       800  .994633549   R-squared       =    0.0127
-------------+----------------------------------   Adj R-squared   =    0.0066
       Total |  805.968682       805  1.00120333   Root MSE        =    .99731

------------------------------------------------------------------------------
         mp2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         wp2 |  -.0733355   .0361606    -2.03   0.043    -.1443164   -.0023545
      female |   .1453268   .0707009     2.06   0.040     .0065455     .284108
         age |  -.0020927   .0027843    -0.75   0.453     -.007558    .0033726
      income |  -.1207916   .1507566    -0.80   0.423    -.4167168    .1751335
  university |    .008304   .0737218     0.11   0.910    -.1364069    .1530149
       _cons |    .055167    .139366     0.40   0.692    -.2183993    .3287333
------------------------------------------------------------------------------
. * Appendix Ideology Alphas
. alpha wp_abortion wp_capitalism wp_gaymarriage wp_guncontrol wp_milspend wp_p
&gt; atriotism wp_socialism if country2==&quot;BR&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0304323
Number of items in the scale:            7
Scale reliability coefficient:      0.6440
. alpha wp_abortion wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_mil
&gt; spend wp_obedience wp_patriotism wp_socialism wp_taxcuts if country2==&quot;CA.e&quot; 
&gt; | country2==&quot;CA.f&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0398736
Number of items in the scale:           10
Scale reliability coefficient:      0.8025
. alpha wp_abortion wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_imm
&gt; igration wp_milspend wp_obedience wp_patriotism wp_socialism if country2==&quot;CH
&gt; &quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0356349
Number of items in the scale:           10
Scale reliability coefficient:      0.7473
. alpha wp_cencorship wp_obedience wp_patriotism wp_women if country2==&quot;CN&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0109147
Number of items in the scale:            4
Scale reliability coefficient:      0.3610
. alpha wp_capitalism wp_deathp wp_guncontrol wp_immigration wp_milspend wp_obe
&gt; dience wp_pollution wp_socialism wp_taxcuts if country2==&quot;DK&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0237862
Number of items in the scale:            9
Scale reliability coefficient:      0.6345
. alpha wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_immigration wp_
&gt; milspend wp_obedience wp_patriotism wp_pollution wp_socialism wp_taxcuts wp_w
&gt; omen if country2==&quot;FR&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:      .030893
Number of items in the scale:           12
Scale reliability coefficient:      0.7698
. alpha wp_deathp wp_gaymarriage wp_obedience wp_patriotism wp_taxcuts if count
&gt; ry2==&quot;GH&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:      .009259
Number of items in the scale:            5
Scale reliability coefficient:      0.3697
. alpha wp_abortion wp_cencorship wp_deathp wp_gaymarriage wp_milspend wp_obedi
&gt; ence wp_patriotism wp_taxcuts if country2==&quot;IN&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0368594
Number of items in the scale:            8
Scale reliability coefficient:      0.6978
. alpha wp_abortion wp_cencorship wp_gaymarriage wp_immigration wp_milspend wp_
&gt; women if country2==&quot;IS.j&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0305129
Number of items in the scale:            6
Scale reliability coefficient:      0.6705
. alpha wp_abortion wp_deathp wp_gaymarriage wp_immigration wp_milspend wp_patr
&gt; iotism wp_socialism if country2==&quot;IS.p&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0260276
Number of items in the scale:            7
Scale reliability coefficient:      0.5707
. alpha wp_abortion wp_capitalism wp_cencorship wp_deathp wp_immigration wp_mil
&gt; spend wp_obedience wp_patriotism wp_pollution wp_women if country2==&quot;IT&quot;
wp_pollution wp_women constant in analysis sample, dropped from analysis

Test scale = mean(unstandardized items)

Average interitem covariance:     .0275767
Number of items in the scale:            8
Scale reliability coefficient:      0.6747
. alpha wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_immigration wp_
&gt; obedience wp_patriotism wp_women if country2==&quot;JP&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:      .022697
Number of items in the scale:            8
Scale reliability coefficient:      0.6484
. alpha wp_capitalism wp_cencorship wp_deathp wp_gaymarriage wp_milspend wp_obe
&gt; dience wp_patriotism wp_pollution wp_socialism wp_taxcuts if country2==&quot;NZ&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0391969
Number of items in the scale:           10
Scale reliability coefficient:      0.7596
. alpha wp_abortion wp_cencorship wp_gaymarriage wp_obedience wp_patriotism wp_
&gt; taxcuts if country2==&quot;RU&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0525538
Number of items in the scale:            6
Scale reliability coefficient:      0.7771
. alpha wp_cencorship wp_obedience wp_patriotism wp_taxcuts if country2==&quot;SE&quot;  
&gt;    

Test scale = mean(unstandardized items)

Average interitem covariance:      .019559
Number of items in the scale:            4
Scale reliability coefficient:      0.3975
. alpha wp_capitalism wp_deathp wp_gaymarriage wp_guncontrol wp_immigration wp_
&gt; milspend wp_obedience wp_patriotism wp_socialism wp_taxcuts if country2==&quot;SW&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0547762
Number of items in the scale:           10
Scale reliability coefficient:      0.8316
. alpha wp_abortion wp_capitalism wp_cencorship wp_gaymarriage wp_immigration w
&gt; p_milspend wp_obedience wp_patriotism wp_taxcuts wp_women if country2==&quot;UK&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0270316
Number of items in the scale:           10
Scale reliability coefficient:      0.7088
. alpha wp_abortion wp_capitalism wp_deathp wp_gaymarriage wp_guncontrol wp_imm
&gt; igration wp_milspend wp_obedience wp_patriotism wp_pollution wp_socialism wp_
&gt; taxcuts if country2==&quot;US&quot;

Test scale = mean(unstandardized items)

Average interitem covariance:     .0327332
Number of items in the scale:           12
Scale reliability coefficient:      0.7766
.   
.   
. * Figure A1
. gen left_right3 = .
(934 missing values generated)
. replace left_right3 = 0 if left_right2 &lt; .5 &amp; left_right2~=.
(402 real changes made)
. replace left_right3 = .5 if left_right2==.5 &amp; left_right2~=.
(181 real changes made)
. replace left_right3 = 1 if left_right2 &gt; .5 &amp; left_right2~=.
(350 real changes made)
. bysort country2: tab left_right3

-------------------------------------------------------------------------------
-&gt; country2 = BR

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         15       42.86       42.86
         .5 |          8       22.86       65.71
          1 |         12       34.29      100.00
------------+-----------------------------------
      Total |         35      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CA.e

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         22       68.75       68.75
         .5 |          6       18.75       87.50
          1 |          4       12.50      100.00
------------+-----------------------------------
      Total |         32      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CA.f

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         20       74.07       74.07
         .5 |          1        3.70       77.78
          1 |          6       22.22      100.00
------------+-----------------------------------
      Total |         27      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CH

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         19       52.78       52.78
         .5 |         13       36.11       88.89
          1 |          4       11.11      100.00
------------+-----------------------------------
      Total |         36      100.00

-------------------------------------------------------------------------------
-&gt; country2 = CN

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |          4        7.14        7.14
         .5 |          5        8.93       16.07
          1 |         47       83.93      100.00
------------+-----------------------------------
      Total |         56      100.00

-------------------------------------------------------------------------------
-&gt; country2 = DK

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         19       54.29       54.29
         .5 |          5       14.29       68.57
          1 |         11       31.43      100.00
------------+-----------------------------------
      Total |         35      100.00

-------------------------------------------------------------------------------
-&gt; country2 = FR

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         22       43.14       43.14
         .5 |          4        7.84       50.98
          1 |         25       49.02      100.00
------------+-----------------------------------
      Total |         51      100.00

-------------------------------------------------------------------------------
-&gt; country2 = GH

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |          5        8.33        8.33
         .5 |         25       41.67       50.00
          1 |         30       50.00      100.00
------------+-----------------------------------
      Total |         60      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IN

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         14       28.00       28.00
         .5 |         12       24.00       52.00
          1 |         24       48.00      100.00
------------+-----------------------------------
      Total |         50      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IS.j

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         30       42.25       42.25
         .5 |          7        9.86       52.11
          1 |         34       47.89      100.00
------------+-----------------------------------
      Total |         71      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IS.p

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |          2        6.25        6.25
         .5 |          4       12.50       18.75
          1 |         26       81.25      100.00
------------+-----------------------------------
      Total |         32      100.00

-------------------------------------------------------------------------------
-&gt; country2 = IT

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         21       56.76       56.76
         .5 |          4       10.81       67.57
          1 |         12       32.43      100.00
------------+-----------------------------------
      Total |         37      100.00

-------------------------------------------------------------------------------
-&gt; country2 = JP

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         15       41.67       41.67
         .5 |         12       33.33       75.00
          1 |          9       25.00      100.00
------------+-----------------------------------
      Total |         36      100.00

-------------------------------------------------------------------------------
-&gt; country2 = NZ

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         21       65.62       65.62
         .5 |          3        9.38       75.00
          1 |          8       25.00      100.00
------------+-----------------------------------
      Total |         32      100.00

-------------------------------------------------------------------------------
-&gt; country2 = RU

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |          9       28.12       28.12
         .5 |         19       59.38       87.50
          1 |          4       12.50      100.00
------------+-----------------------------------
      Total |         32      100.00

-------------------------------------------------------------------------------
-&gt; country2 = SE

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         19       39.58       39.58
         .5 |         15       31.25       70.83
          1 |         14       29.17      100.00
------------+-----------------------------------
      Total |         48      100.00

-------------------------------------------------------------------------------
-&gt; country2 = SW

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         15       48.39       48.39
         .5 |          3        9.68       58.06
          1 |         13       41.94      100.00
------------+-----------------------------------
      Total |         31      100.00

-------------------------------------------------------------------------------
-&gt; country2 = UK

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         25       52.08       52.08
         .5 |         15       31.25       83.33
          1 |          8       16.67      100.00
------------+-----------------------------------
      Total |         48      100.00

-------------------------------------------------------------------------------
-&gt; country2 = US

left_right3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |        105       57.07       57.07
         .5 |         20       10.87       67.93
          1 |         59       32.07      100.00
------------+-----------------------------------
      Total |        184      100.00

.   
. * Table A1
. sum age female income university english_prof wp_right2

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |        933    29.18435    12.23282         16         74
      female |        934    .5299786    .4993679          0          1
      income |        934    .5444326     .235109          0          1
  university |        934    .6573876    .4748374          0          1
english_prof |        934    5.392934    1.888872          1          7
-------------+---------------------------------------------------------
   wp_right2 |        934    .3876842    .2256694          0   .8888889
. bysort country2: sum age female income university english_prof wp_right2

-------------------------------------------------------------------------------
-&gt; country2 = BR

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         35    25.57143     5.68427         18         42
      female |         35    .5714286    .5020964          0          1
      income |         35    .5619048    .2289708          0          1
  university |         35    .6857143    .4710082          0          1
english_prof |         35    4.085714    2.119537          1          7
-------------+---------------------------------------------------------
   wp_right2 |         35    .3589286    .1889301          0        .75

-------------------------------------------------------------------------------
-&gt; country2 = CA.e

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         32    22.90625    4.357858         18         40
      female |         32       .6875    .4709291          0          1
      income |         32    .5052083     .248596          0          1
  university |         32        .875    .3360108          0          1
english_prof |         32     6.78125    .5526695          5          7
-------------+---------------------------------------------------------
   wp_right2 |         32    .2197917    .1917137          0         .8

-------------------------------------------------------------------------------
-&gt; country2 = CA.f

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         27    35.14815    13.88054         17         63
      female |         27    .2962963    .4653216          0          1
      income |         27    .5432099    .2147976   .1666667   .8333333
  university |         27    .7777778    .4236593          0          1
english_prof |         27    6.222222    1.187542          3          7
-------------+---------------------------------------------------------
   wp_right2 |         27     .252862    .2171309          0   .7272727

-------------------------------------------------------------------------------
-&gt; country2 = CH

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         36    36.88889    12.42987         20         66
      female |         36          .5    .5070926          0          1
      income |         36    .4074074    .1844961   .1666667   .8333333
  university |         36    .5833333          .5          0          1
english_prof |         36    3.222222    2.139574          1          7
-------------+---------------------------------------------------------
   wp_right2 |         36    .3131313    .1985121          0   .7727273

-------------------------------------------------------------------------------
-&gt; country2 = CN

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         56    26.03571    4.805165         19         39
      female |         56    .4821429    .5042031          0          1
      income |         56    .4434524    .1914242          0          1
  university |         56        .875    .3337119          0          1
english_prof |         56       3.875    1.549927          1          7
-------------+---------------------------------------------------------
   wp_right2 |         56    .4946429    .1380641          0         .7

-------------------------------------------------------------------------------
-&gt; country2 = DK

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         35    34.57143    14.44317         21         64
      female |         35          .4    .4970501          0          1
      income |         35    .5952381    .2187521          0          1
  university |         35    .6857143    .4710082          0          1
english_prof |         35    5.514286    1.221653          2          7
-------------+---------------------------------------------------------
   wp_right2 |         35    .2914286    .1742571        .05         .6

-------------------------------------------------------------------------------
-&gt; country2 = FR

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         51     27.2549    10.47634         16         58
      female |         51    .4901961    .5048782          0          1
      income |         51     .627451    .2175322          0          1
  university |         51    .5098039    .5048782          0          1
english_prof |         51    5.411765    1.251822          2          7
-------------+---------------------------------------------------------
   wp_right2 |         51    .3556435    .1841998   .0384615   .7692308

-------------------------------------------------------------------------------
-&gt; country2 = GH

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         60       31.05    10.42881         18         67
      female |         61    .5409836     .502453          0          1
      income |         61    .5218579    .2480954          0          1
  university |         61    .4918033    .5040817          0          1
english_prof |         61    5.540984    1.455722          1          7
-------------+---------------------------------------------------------
   wp_right2 |         61     .629235    .1738895          0   .8333333

-------------------------------------------------------------------------------
-&gt; country2 = IN

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         50       33.16    8.266875         22         53
      female |         50          .4    .4948717          0          1
      income |         50    .4933333    .2607333          0          1
  university |         50         .38    .4903144          0          1
english_prof |         50           4    2.118914          1          7
-------------+---------------------------------------------------------
   wp_right2 |         50    .6031944    .2190013          0   .8888889

-------------------------------------------------------------------------------
-&gt; country2 = IS.j

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         71    23.94366    3.134542         17         33
      female |         71    .5070423    .5035088          0          1
      income |         71    .5798122    .2161333          0          1
  university |         71    .8591549    .3503376          0          1
english_prof |         71    5.957746    1.235622          1          7
-------------+---------------------------------------------------------
   wp_right2 |         71    .2194836    .1827042          0   .7142857

-------------------------------------------------------------------------------
-&gt; country2 = IS.p

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         32          19    2.109885         16         25
      female |         32      .59375    .4989909          0          1
      income |         32       .4375    .2148184          0   .8333333
  university |         32       .9375    .2459347          0          1
english_prof |         32      5.1875    1.533234          1          7
-------------+---------------------------------------------------------
   wp_right2 |         32    .3560268    .1874486          0       .875

-------------------------------------------------------------------------------
-&gt; country2 = IT

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         37    24.35135    5.954532         20         57
      female |         37    .6756757     .474579          0          1
      income |         37    .5720721    .1645258   .1666667   .8333333
  university |         37    .8918919    .3148001          0          1
english_prof |         37    5.567568    1.344547          1          7
-------------+---------------------------------------------------------
   wp_right2 |         37    .2444717    .1470366          0         .5

-------------------------------------------------------------------------------
-&gt; country2 = JP

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         36        21.5    1.664761         18         26
      female |         36    .4444444    .5039526          0          1
      income |         36    .5324074    .2482301          0          1
  university |         36    .8888889    .3187276          0          1
english_prof |         36         3.5    1.594634          1          7
-------------+---------------------------------------------------------
   wp_right2 |         36    .3503086    .1663062          0   .7777778

-------------------------------------------------------------------------------
-&gt; country2 = NZ

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         32    45.65625    17.70112         21         66
      female |         32       .4375    .5040161          0          1
      income |         32        .625    .2710659          0          1
  university |         32       .6875    .4709291          0          1
english_prof |         32      6.9375    .2459347          6          7
-------------+---------------------------------------------------------
   wp_right2 |         32    .3210227    .2065114          0   .7272727

-------------------------------------------------------------------------------
-&gt; country2 = RU

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         32     29.9375    10.11526         20         59
      female |         32      .59375    .4989909          0          1
      income |         32      .40625    .1982789          0   .6666667
  university |         32        .875    .3360108          0          1
english_prof |         32       3.625    1.979736          1          7
-------------+---------------------------------------------------------
   wp_right2 |         32    .5669643    .2228972          0   .8571429

-------------------------------------------------------------------------------
-&gt; country2 = SE

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         48    31.04167    10.09942         18         63
      female |         48    .3333333    .4763931          0          1
      income |         48    .5104167    .1627419          0          1
  university |         48    .3541667    .4833211          0          1
english_prof |         48    2.833333    1.667376          1          7
-------------+---------------------------------------------------------
   wp_right2 |         48          .6    .1774524         .2         .8

-------------------------------------------------------------------------------
-&gt; country2 = SW

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         31    44.22581    13.72032         24         66
      female |         31    .4516129    .5058794          0          1
      income |         31    .6344086     .203758   .1666667          1
  university |         31    .6129032    .4951376          0          1
english_prof |         31    5.645161    .9146361          4          7
-------------+---------------------------------------------------------
   wp_right2 |         31    .3197947    .2332503          0   .8181818

-------------------------------------------------------------------------------
-&gt; country2 = UK

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |         48    40.83333    14.97421         19         74
      female |         48        .625    .4892461          0          1
      income |         48    .4826389    .2484933          0          1
  university |         48    .2291667    .4247444          0          1
english_prof |         48    6.791667    .5441501          4          7
-------------+---------------------------------------------------------
   wp_right2 |         48    .2989583    .1877894          0        .65

-------------------------------------------------------------------------------
-&gt; country2 = US

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         age |        184    24.57609    11.81528         17         68
      female |        184    .6467391    .4792871          0          1
      income |        184     .615942    .2460855          0          1
  university |        184    .6467391    .4792871          0          1
english_prof |        184    6.918478    .3895996          3          7
-------------+---------------------------------------------------------
   wp_right2 |        184    .3788496    .1894891   .0384615   .8846154

. * Table A3 Row 1
. quietly regress mean_dif2 wp_right2 female age income university 
. estimates store A
. quietly regress mean_dif3 wp_right2 female age income university 
. estimates store B
. esttab A B , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)

--------------------------------------------
                      (1)             (2)   
                mean_dif2       mean_dif3   
                     b/se            b/se   
--------------------------------------------
wp_right2           0.104          -0.172   
                  (0.093)         (0.157)   
female             -0.023          -0.016   
                  (0.042)         (0.071)   
age                -0.003          -0.002   
                  (0.002)         (0.003)   
income              0.086          -0.061   
                  (0.088)         (0.149)   
university         -0.054           0.015   
                  (0.044)         (0.075)   
_cons               0.131           0.152   
                  (0.093)         (0.157)   
--------------------------------------------
r2                  0.007           0.002   
r2_a                0.002          -0.003   
N                 933.000         933.000   
--------------------------------------------
.   
. * Table A4 Row 1 
. quietly regress mean_ph_dif_all wp_right2 female age income university  
. estimates store A
. quietly regress mean_ph_dif3_all wp_right2 female age income university  
. estimates store B
. quietly regress mean_ph_dif2_all wp_right2 female age income university  
. estimates store C
. esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)

------------------------------------------------------------
                      (1)             (2)             (3)   
             mean_p~f_all    mean_p~3_all    mean_p~2_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
wp_right2          -0.069*         -0.074          -0.053   
                  (0.034)         (0.042)         (0.042)   
female              0.031*          0.027           0.042*  
                  (0.015)         (0.018)         (0.019)   
age                -0.000          -0.001          -0.000   
                  (0.001)         (0.001)         (0.001)   
income             -0.026          -0.009          -0.059   
                  (0.032)         (0.039)         (0.039)   
university          0.002           0.010          -0.004   
                  (0.016)         (0.019)         (0.019)   
_cons               0.073*          0.068           0.077   
                  (0.033)         (0.041)         (0.041)   
------------------------------------------------------------
r2                  0.013           0.009           0.012   
r2_a                0.007           0.003           0.005   
N                 806.000         795.000         796.000   
------------------------------------------------------------
.                 
. * Table A6 Row 1
.   
.   gen right2 = .
(934 missing values generated)
.   replace right2= wp_right2
(934 real changes made)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store A
.   replace right2= wp_right2_dicho2
(890 real changes made)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store B  
.   replace right2= wp_right2_dichox
(264 real changes made)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store C
.   replace right2= left_right2
(879 real changes made, 1 to missing)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store D
.   replace right2= left_right2_dichox
(841 real changes made)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store E 
.   replace right2= ideo_right2
(929 real changes made)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store F
.   replace right2= ideo_right2_dichox
(929 real changes made)
.   quietly regress mean_dif2 right2 female age income university  
.   estimates store G  
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)  

------------------------------------------------------------
                      (1)             (2)             (3)   
                mean_dif2       mean_dif2       mean_dif2   
                     b/se            b/se            b/se   
------------------------------------------------------------
right2              0.104           0.006           0.022   
                  (0.093)         (0.044)         (0.042)   
female             -0.023          -0.025          -0.024   
                  (0.042)         (0.042)         (0.042)   
age                -0.003          -0.003          -0.003   
                  (0.002)         (0.002)         (0.002)   
income              0.086           0.081           0.078   
                  (0.088)         (0.088)         (0.088)   
university         -0.054          -0.060          -0.059   
                  (0.044)         (0.044)         (0.044)   
_cons               0.131           0.173*          0.166   
                  (0.093)         (0.085)         (0.085)   
------------------------------------------------------------
r2_w                                                        
r2_b                                                        
r2_o                                                        
N                 933.000         933.000         933.000   
N_g                                                         
------------------------------------------------------------
.   esttab D E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g)  

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                mean_dif2       mean_dif2       mean_dif2       mean_dif2   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
right2              0.100           0.052           0.144           0.104*  
                  (0.080)         (0.042)         (0.102)         (0.041)   
female             -0.022          -0.024          -0.022          -0.023   
                  (0.042)         (0.042)         (0.042)         (0.042)   
age                -0.003          -0.003          -0.003          -0.003   
                  (0.002)         (0.002)         (0.002)         (0.002)   
income              0.078           0.073           0.082           0.071   
                  (0.088)         (0.088)         (0.088)         (0.088)   
university         -0.059          -0.057          -0.055          -0.055   
                  (0.044)         (0.044)         (0.044)         (0.044)   
_cons               0.125           0.151           0.108           0.128   
                  (0.093)         (0.086)         (0.097)         (0.085)   
----------------------------------------------------------------------------
r2_w                                                                        
r2_b                                                                        
r2_o                                                                        
N                 932.000         932.000         932.000         932.000   
N_g                                                                         
----------------------------------------------------------------------------
.   
.   
. * Table A6 Row 4 
.   replace right2= wp_right2
(898 real changes made)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store A
.   replace right2= wp_right2_dicho2
(890 real changes made)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store B
.   replace right2= wp_right2_dichox
(264 real changes made)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store C
.   replace right2= left_right2
(879 real changes made, 1 to missing)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store D  
.   replace right2= left_right2_dichox
(841 real changes made)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store E
.   replace right2= ideo_right2
(929 real changes made)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store F
.   replace right2= ideo_right2_dichox
(929 real changes made)
.   quietly regress mean_ph_dif_all right2 female age income university  
.   estimates store G
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)  

------------------------------------------------------------
                      (1)             (2)             (3)   
             mean_p~f_all    mean_p~f_all    mean_p~f_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
right2             -0.069*         -0.037*         -0.018   
                  (0.034)         (0.016)         (0.015)   
female              0.031*          0.030*          0.031*  
                  (0.015)         (0.015)         (0.015)   
age                -0.000          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
income             -0.026          -0.027          -0.019   
                  (0.032)         (0.032)         (0.032)   
university          0.002           0.003           0.005   
                  (0.016)         (0.016)         (0.016)   
_cons               0.073*          0.058           0.049   
                  (0.033)         (0.030)         (0.030)   
------------------------------------------------------------
r2_w                                                        
r2_b                                                        
r2_o                                                        
N                 806.000         806.000         806.000   
N_g                                                         
------------------------------------------------------------
.   esttab D E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g)  

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
             mean_p~f_all    mean_p~f_all    mean_p~f_all    mean_p~f_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
right2             -0.041           0.013          -0.074*         -0.012   
                  (0.029)         (0.015)         (0.037)         (0.015)   
female              0.031*          0.032*          0.031*          0.032*  
                  (0.015)         (0.015)         (0.015)         (0.015)   
age                -0.001          -0.001          -0.001          -0.000   
                  (0.001)         (0.001)         (0.001)         (0.001)   
income             -0.020          -0.023          -0.023          -0.020   
                  (0.032)         (0.032)         (0.032)         (0.032)   
university          0.005           0.006           0.003           0.004   
                  (0.016)         (0.016)         (0.016)         (0.016)   
_cons               0.063           0.035           0.078*          0.047   
                  (0.033)         (0.030)         (0.035)         (0.030)   
----------------------------------------------------------------------------
r2_w                                                                        
r2_b                                                                        
r2_o                                                                        
N                 805.000         805.000         805.000         805.000   
N_g                                                                         
----------------------------------------------------------------------------
.          
.  
. * Table A7
.   
. regress mean_dif2 wp_right2 female age income university  

      Source |       SS           df       MS      Number of obs   =       933
-------------+----------------------------------   F(5, 927)       =      1.34
       Model |   2.6843355         5    .5368671   Prob &gt; F        =    0.2430
    Residual |  370.026446       927  .399165529   R-squared       =    0.0072
-------------+----------------------------------   Adj R-squared   =    0.0018
       Total |  372.710781       932  .399904272   Root MSE        =     .6318

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   wp_right2 |   .1035859    .093023     1.11   0.266    -.0789742     .286146
      female |  -.0230074   .0418745    -0.55   0.583    -.1051873    .0591724
         age |  -.0031561   .0017191    -1.84   0.067    -.0065298    .0002176
      income |   .0856957   .0881939     0.97   0.331     -.087387    .2587785
  university |  -.0540114   .0442642    -1.22   0.223    -.1408811    .0328583
       _cons |    .130539   .0926448     1.41   0.159    -.0512788    .3123568
------------------------------------------------------------------------------
. regress mean_dif2 wp_abortion female age income university   

      Source |       SS           df       MS      Number of obs   =       927
-------------+----------------------------------   F(5, 921)       =      1.18
       Model |  2.36393206         5  .472786412   Prob &gt; F        =    0.3184
    Residual |  369.883365       921  .401610603   R-squared       =    0.0064
-------------+----------------------------------   Adj R-squared   =    0.0010
       Total |  372.247297       926  .401994922   Root MSE        =    .63373

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 wp_abortion |   .0312297   .0491651     0.64   0.525     -.065259    .1277183
      female |  -.0259391    .042091    -0.62   0.538    -.1085446    .0566664
         age |  -.0030929   .0017256    -1.79   0.073    -.0064795    .0002936
      income |   .0856217   .0887781     0.96   0.335    -.0886093    .2598526
  university |   -.057719   .0444389    -1.30   0.194    -.1449323    .0294942
       _cons |   .1629146    .086651     1.88   0.060    -.0071417    .3329709
------------------------------------------------------------------------------
. regress mean_dif2 wp_capitalism female age income university  

      Source |       SS           df       MS      Number of obs   =       925
-------------+----------------------------------   F(5, 919)       =      1.07
       Model |  2.15738906         5  .431477812   Prob &gt; F        =    0.3738
    Residual |   369.54926       919  .402121066   R-squared       =    0.0058
-------------+----------------------------------   Adj R-squared   =    0.0004
       Total |  371.706649       924  .402279923   Root MSE        =    .63413

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_capital~m |   .0080723     .05153     0.16   0.876    -.0930578    .1092024
      female |  -.0250712    .042318    -0.59   0.554    -.1081223    .0579799
         age |  -.0030484   .0017252    -1.77   0.078    -.0064341    .0003373
      income |   .0807063   .0903861     0.89   0.372    -.0966808    .2580935
  university |  -.0580861   .0444095    -1.31   0.191    -.1452419    .0290697
       _cons |   .1694028   .0867478     1.95   0.051    -.0008439    .3396496
------------------------------------------------------------------------------
. regress mean_dif2 wp_cencorship female age income university  

      Source |       SS           df       MS      Number of obs   =       922
-------------+----------------------------------   F(5, 916)       =      1.32
       Model |  2.65212649         5  .530425298   Prob &gt; F        =    0.2544
    Residual |  368.913301       916  .402743778   R-squared       =    0.0071
-------------+----------------------------------   Adj R-squared   =    0.0017
       Total |  371.565427       921  .403436946   Root MSE        =    .63462

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_cencors~p |  -.0547273   .0495933    -1.10   0.270    -.1520569    .0426023
      female |  -.0235865   .0423143    -0.56   0.577    -.1066307    .0594577
         age |  -.0032203   .0017339    -1.86   0.064    -.0066232    .0001826
      income |   .0741825   .0894133     0.83   0.407    -.1012963    .2496612
  university |   -.059936   .0445637    -1.34   0.179    -.1473948    .0275227
       _cons |   .2016417   .0881346     2.29   0.022     .0286726    .3746109
------------------------------------------------------------------------------
. regress mean_dif2 wp_deathp female age income university  

      Source |       SS           df       MS      Number of obs   =       926
-------------+----------------------------------   F(5, 920)       =      1.67
       Model |  3.35214734         5  .670429467   Prob &gt; F        =    0.1387
    Residual |  368.891467       920  .400968986   R-squared       =    0.0090
-------------+----------------------------------   Adj R-squared   =    0.0036
       Total |  372.243614       925  .402425529   Root MSE        =    .63322

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   wp_deathp |   .0796663   .0474724     1.68   0.094    -.0135005    .1728331
      female |  -.0278627   .0420944    -0.66   0.508    -.1104749    .0547495
         age |  -.0028224   .0017314    -1.63   0.103    -.0062204    .0005756
      income |   .0996175   .0892251     1.12   0.265    -.0754907    .2747258
  university |  -.0545487   .0444678    -1.23   0.220    -.1418189    .0327214
       _cons |   .1258034   .0889922     1.41   0.158    -.0488478    .3004546
------------------------------------------------------------------------------
. regress mean_dif2 wp_gaymarriage female age income university  

      Source |       SS           df       MS      Number of obs   =       925
-------------+----------------------------------   F(5, 919)       =      1.13
       Model |  2.26814942         5  .453629885   Prob &gt; F        =    0.3428
    Residual |   369.02527       919  .401550892   R-squared       =    0.0061
-------------+----------------------------------   Adj R-squared   =    0.0007
       Total |  371.293419       924  .401832705   Root MSE        =    .63368

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_gaymarr~e |  -.0049728   .0494871    -0.10   0.920    -.1020937    .0921481
      female |  -.0247821   .0422338    -0.59   0.557    -.1076679    .0581038
         age |  -.0031186   .0017287    -1.80   0.072    -.0065113    .0002742
      income |   .0874685   .0892838     0.98   0.328    -.0877554    .2626924
  university |  -.0602069   .0446771    -1.35   0.178    -.1478879    .0274742
       _cons |   .1761676   .0865548     2.04   0.042     .0062996    .3460356
------------------------------------------------------------------------------
. regress mean_dif2 wp_guncontrol female age income university  

      Source |       SS           df       MS      Number of obs   =       927
-------------+----------------------------------   F(5, 921)       =      1.16
       Model |  2.32188711         5  .464377423   Prob &gt; F        =    0.3290
    Residual |  369.928455       921   .40165956   R-squared       =    0.0062
-------------+----------------------------------   Adj R-squared   =    0.0008
       Total |  372.250342       926  .401998209   Root MSE        =    .63377

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_guncont~l |   .0330061   .0632534     0.52   0.602    -.0911314    .1571436
      female |   -.025081   .0421359    -0.60   0.552    -.1077746    .0576126
         age |  -.0030578   .0017265    -1.77   0.077    -.0064462    .0003305
      income |   .0821513   .0885553     0.93   0.354    -.0916424    .2559449
  university |   -.059808   .0443209    -1.35   0.178    -.1467896    .0271736
       _cons |   .1697745   .0848364     2.00   0.046     .0032795    .3362695
------------------------------------------------------------------------------
. regress mean_dif2 wp_immigration female age income university  

      Source |       SS           df       MS      Number of obs   =       919
-------------+----------------------------------   F(5, 913)       =      1.49
       Model |  2.99862732         5  .599725465   Prob &gt; F        =    0.1908
    Residual |  367.742027       913  .402784258   R-squared       =    0.0081
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  370.740655       918  .403856922   Root MSE        =    .63465

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_immigra~n |   .0781715    .052567     1.49   0.137    -.0249947    .1813377
      female |   -.018295   .0423973    -0.43   0.666    -.1015026    .0649126
         age |  -.0030497   .0017322    -1.76   0.079    -.0064493    .0003499
      income |   .0927517   .0893628     1.04   0.300    -.0826285     .268132
  university |  -.0596839   .0446357    -1.34   0.182    -.1472844    .0279166
       _cons |    .141495   .0866173     1.63   0.103     -.028497    .3114871
------------------------------------------------------------------------------
. regress mean_dif2 wp_milspend female age income university  

      Source |       SS           df       MS      Number of obs   =       870
-------------+----------------------------------   F(5, 864)       =      1.28
       Model |  2.58845606         5  .517691213   Prob &gt; F        =    0.2709
    Residual |  349.822015       864  .404886592   R-squared       =    0.0073
-------------+----------------------------------   Adj R-squared   =    0.0016
       Total |  352.410471       869   .40553564   Root MSE        =    .63631

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 wp_milspend |   .0004983   .0496102     0.01   0.992    -.0968722    .0978689
      female |  -.0486619   .0437016    -1.11   0.266    -.1344357    .0371119
         age |  -.0030825   .0017435    -1.77   0.077    -.0065045    .0003395
      income |   .0941649   .0913333     1.03   0.303    -.0850962     .273426
  university |  -.0628112   .0457349    -1.37   0.170    -.1525757    .0269533
       _cons |   .1817194    .089807     2.02   0.043     .0054539    .3579849
------------------------------------------------------------------------------
. regress mean_dif2 wp_obedience female age income university  

      Source |       SS           df       MS      Number of obs   =       926
-------------+----------------------------------   F(5, 920)       =      1.09
       Model |  2.18991158         5  .437982316   Prob &gt; F        =    0.3622
    Residual |  368.420554       920  .400457124   R-squared       =    0.0059
-------------+----------------------------------   Adj R-squared   =    0.0005
       Total |  370.610466       925  .400659963   Root MSE        =    .63282

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_obedience |   .0049176   .0506241     0.10   0.923    -.0944345    .1042696
      female |  -.0301084    .042078    -0.72   0.474    -.1126883    .0524715
         age |  -.0031424   .0017259    -1.82   0.069    -.0065296    .0002447
      income |   .0718968   .0885537     0.81   0.417    -.1018938    .2456874
  university |  -.0585365   .0446278    -1.31   0.190    -.1461207    .0290477
       _cons |   .1825114    .088181     2.07   0.039     .0094521    .3555707
------------------------------------------------------------------------------
. regress mean_dif2 wp_patriotism female age income university  

      Source |       SS           df       MS      Number of obs   =       926
-------------+----------------------------------   F(5, 920)       =      2.17
       Model |  4.33346627         5  .866693255   Prob &gt; F        =    0.0557
    Residual |  367.858326       920  .399846007   R-squared       =    0.0116
-------------+----------------------------------   Adj R-squared   =    0.0063
       Total |  372.191793       925  .402369506   Root MSE        =    .63233

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_patriot~m |   .1229144   .0523242     2.35   0.019     .0202258     .225603
      female |    -.02639   .0420281    -0.63   0.530    -.1088721    .0560921
         age |  -.0028238   .0017246    -1.64   0.102    -.0062084    .0005608
      income |   .0825506   .0884063     0.93   0.351    -.0909508     .256052
  university |  -.0568498   .0442149    -1.29   0.199    -.1436235     .029924
       _cons |   .0792248   .0926701     0.85   0.393    -.1026445    .2610941
------------------------------------------------------------------------------
. regress mean_dif2 wp_pollution female age income university  

      Source |       SS           df       MS      Number of obs   =       927
-------------+----------------------------------   F(5, 921)       =      1.08
       Model |  2.17618409         5  .435236818   Prob &gt; F        =    0.3679
    Residual |  369.963237       921  .401697326   R-squared       =    0.0058
-------------+----------------------------------   Adj R-squared   =    0.0005
       Total |  372.139421       926  .401878425   Root MSE        =     .6338

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_pollution |  -.0189365   .0812478    -0.23   0.816    -.1783889    .1405159
      female |  -.0252852   .0421143    -0.60   0.548    -.1079362    .0573659
         age |  -.0030541   .0017273    -1.77   0.077     -.006444    .0003359
      income |   .0798742   .0884837     0.90   0.367    -.0937789    .2535273
  university |  -.0595172   .0443107    -1.34   0.180    -.1464788    .0274444
       _cons |    .176897   .0845143     2.09   0.037     .0110341    .3427599
------------------------------------------------------------------------------
. regress mean_dif2 wp_socialism female age income university  

      Source |       SS           df       MS      Number of obs   =       923
-------------+----------------------------------   F(5, 917)       =      1.09
       Model |  2.19218236         5  .438436472   Prob &gt; F        =    0.3653
    Residual |  369.498268       917  .402942495   R-squared       =    0.0059
-------------+----------------------------------   Adj R-squared   =    0.0005
       Total |   371.69045       922  .403134979   Root MSE        =    .63478

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_socialism |   .0182944   .0511999     0.36   0.721    -.0821883    .1187771
      female |  -.0240771   .0423663    -0.57   0.570    -.1072231     .059069
         age |  -.0030439    .001731    -1.76   0.079     -.006441    .0003532
      income |   .0816932   .0888926     0.92   0.358    -.0927633    .2561497
  university |   -.058738   .0445392    -1.32   0.188    -.1461486    .0286726
       _cons |   .1657011   .0863104     1.92   0.055    -.0036878      .33509
------------------------------------------------------------------------------
. regress mean_dif2 wp_taxcuts female age income university  

      Source |       SS           df       MS      Number of obs   =       921
-------------+----------------------------------   F(5, 915)       =      1.11
       Model |  2.21724982         5  .443449964   Prob &gt; F        =    0.3526
    Residual |  365.108831       915  .399026044   R-squared       =    0.0060
-------------+----------------------------------   Adj R-squared   =    0.0006
       Total |   367.32608       920  .399267479   Root MSE        =    .63169

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  wp_taxcuts |   .0142807   .0500518     0.29   0.775     -.083949    .1125104
      female |  -.0248354    .042093    -0.59   0.555    -.1074455    .0577747
         age |  -.0031243   .0017273    -1.81   0.071    -.0065143    .0002657
      income |   .0868977   .0885271     0.98   0.327    -.0868421    .2606375
  university |  -.0553634   .0442648    -1.25   0.211    -.1422357    .0315089
       _cons |   .1653938   .0911694     1.81   0.070    -.0135317    .3443192
------------------------------------------------------------------------------
. regress mean_dif2 wp_women female age income university 

      Source |       SS           df       MS      Number of obs   =       926
-------------+----------------------------------   F(5, 920)       =      1.37
       Model |  2.75063385         5  .550126769   Prob &gt; F        =    0.2327
    Residual |  369.089887       920   .40118466   R-squared       =    0.0074
-------------+----------------------------------   Adj R-squared   =    0.0020
       Total |  371.840521       925  .401989753   Root MSE        =    .63339

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    wp_women |    .102437   .0900127     1.14   0.255    -.0742171    .2790911
      female |  -.0202705   .0422945    -0.48   0.632    -.1032753    .0627343
         age |  -.0032274   .0017266    -1.87   0.062    -.0066159    .0001611
      income |   .0809298    .088928     0.91   0.363    -.0935955     .255455
  university |  -.0593109   .0443245    -1.34   0.181    -.1462997    .0276779
       _cons |   .1704788   .0846558     2.01   0.044     .0043379    .3366196
------------------------------------------------------------------------------
.   
. regress mean_ph_dif3_all wp_right2 female age income university  

      Source |       SS           df       MS      Number of obs   =       795
-------------+----------------------------------   F(5, 789)       =      1.40
       Model |  .461488476         5  .092297695   Prob &gt; F        =    0.2215
    Residual |  51.9688475       789  .065866727   R-squared       =    0.0088
-------------+----------------------------------   Adj R-squared   =    0.0025
       Total |  52.4303359       794  .066033169   Root MSE        =    .25665

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   wp_right2 |  -.0741532    .041523    -1.79   0.075    -.1556618    .0073554
      female |   .0265993   .0183138     1.45   0.147    -.0093502    .0625487
         age |  -.0005056   .0007245    -0.70   0.485    -.0019279    .0009166
      income |  -.0090882   .0388963    -0.23   0.815    -.0854408    .0672644
  university |   .0100965   .0191123     0.53   0.597    -.0274204    .0476134
       _cons |   .0677992    .040596     1.67   0.095    -.0118897     .147488
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_abortion female age income university   

      Source |       SS           df       MS      Number of obs   =       790
-------------+----------------------------------   F(5, 784)       =      1.06
       Model |  .352697159         5  .070539432   Prob &gt; F        =    0.3797
    Residual |   52.042024       784  .066380133   R-squared       =    0.0067
-------------+----------------------------------   Adj R-squared   =    0.0004
       Total |  52.3947212       789  .066406491   Root MSE        =    .25764

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 wp_abortion |  -.0274342   .0214302    -1.28   0.201    -.0695016    .0146332
      female |   .0273894   .0184392     1.49   0.138    -.0088067    .0635854
         age |  -.0005564   .0007281    -0.76   0.445    -.0019857    .0008728
      income |   -.009546   .0391664    -0.24   0.808    -.0864295    .0673375
  university |   .0112476   .0192385     0.58   0.559    -.0265175    .0490127
       _cons |   .0479071   .0375749     1.27   0.203    -.0258522    .1216665
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_capitalism female age income university  

      Source |       SS           df       MS      Number of obs   =       787
-------------+----------------------------------   F(5, 781)       =      0.76
       Model |  .252774441         5  .050554888   Prob &gt; F        =    0.5797
    Residual |  52.0362687       781  .066627745   R-squared       =    0.0048
-------------+----------------------------------   Adj R-squared   =   -0.0015
       Total |  52.2890431       786    .0665255   Root MSE        =    .25812

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_capital~m |  -.0049791   .0226977    -0.22   0.826    -.0495347    .0395766
      female |   .0272207   .0185754     1.47   0.143    -.0092429    .0636842
         age |  -.0006051   .0007287    -0.83   0.407    -.0020354    .0008253
      income |  -.0036283   .0399677    -0.09   0.928    -.0820853    .0748286
  university |    .012348   .0192586     0.64   0.522    -.0254567    .0501527
       _cons |    .038847   .0373981     1.04   0.299    -.0345657    .1122597
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_cencorship female age income university  

      Source |       SS           df       MS      Number of obs   =       785
-------------+----------------------------------   F(5, 779)       =      2.86
       Model |  .942526649         5   .18850533   Prob &gt; F        =    0.0145
    Residual |  51.4223402       779  .066010706   R-squared       =    0.0180
-------------+----------------------------------   Adj R-squared   =    0.0117
       Total |  52.3648668       784  .066791922   Root MSE        =    .25693

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_cencors~p |  -.0700174   .0216417    -3.24   0.001    -.1125002   -.0275345
      female |   .0313801   .0184859     1.70   0.090     -.004908    .0676681
         age |  -.0007929   .0007294    -1.09   0.277    -.0022248    .0006389
      income |  -.0244134   .0394664    -0.62   0.536    -.1018865    .0530597
  university |   .0101411   .0192315     0.53   0.598    -.0276106    .0478928
       _cons |   .0772322   .0384377     2.01   0.045     .0017785    .1526859
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_deathp female age income university  

      Source |       SS           df       MS      Number of obs   =       788
-------------+----------------------------------   F(5, 782)       =      0.99
       Model |   .33018586         5  .066037172   Prob &gt; F        =    0.4214
    Residual |  52.0474156       782  .066556797   R-squared       =    0.0063
-------------+----------------------------------   Adj R-squared   =   -0.0000
       Total |  52.3776014       787  .066553496   Root MSE        =    .25799

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   wp_deathp |  -.0224191   .0210415    -1.07   0.287    -.0637237    .0188854
      female |   .0281312   .0184938     1.52   0.129    -.0081722    .0644346
         age |  -.0006475   .0007318    -0.88   0.377     -.002084     .000789
      income |  -.0120053   .0395501    -0.30   0.762    -.0896422    .0656315
  university |   .0125064   .0192892     0.65   0.517    -.0253583     .050371
       _cons |   .0501427   .0387033     1.30   0.196    -.0258319    .1261173
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_gaymarriage female age income university  

      Source |       SS           df       MS      Number of obs   =       787
-------------+----------------------------------   F(5, 781)       =      1.27
       Model |  .419178565         5  .083835713   Prob &gt; F        =    0.2769
    Residual |  51.7477981       781  .066258384   R-squared       =    0.0080
-------------+----------------------------------   Adj R-squared   =    0.0017
       Total |  52.1669766       786  .066370199   Root MSE        =    .25741

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_gaymarr~e |  -.0312377   .0213298    -1.46   0.143    -.0731082    .0106327
      female |   .0269048   .0184845     1.46   0.146    -.0093804      .06319
         age |  -.0005614   .0007288    -0.77   0.441    -.0019919    .0008692
      income |  -.0107495   .0394813    -0.27   0.785    -.0882515    .0667526
  university |   .0114576   .0193406     0.59   0.554    -.0265082    .0494233
       _cons |   .0496638   .0376607     1.32   0.188    -.0242644     .123592
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_guncontrol female age income university  

      Source |       SS           df       MS      Number of obs   =       789
-------------+----------------------------------   F(5, 783)       =      0.74
       Model |  .247487414         5  .049497483   Prob &gt; F        =    0.5912
    Residual |  52.1471773       783  .066599205   R-squared       =    0.0047
-------------+----------------------------------   Adj R-squared   =   -0.0016
       Total |  52.3946647       788  .066490691   Root MSE        =    .25807

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_guncont~l |   .0053669   .0280652     0.19   0.848    -.0497251    .0604588
      female |   .0271983   .0184929     1.47   0.142    -.0091032    .0634999
         age |  -.0005667   .0007295    -0.78   0.438    -.0019986    .0008653
      income |  -.0044872   .0391158    -0.11   0.909    -.0812716    .0722971
  university |   .0138317   .0192277     0.72   0.472    -.0239123    .0515757
       _cons |   .0341116   .0367757     0.93   0.354     -.038079    .1063023
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_immigration female age income university  

      Source |       SS           df       MS      Number of obs   =       781
-------------+----------------------------------   F(5, 775)       =      0.77
       Model |   .25918723         5  .051837446   Prob &gt; F        =    0.5705
    Residual |  52.0819213       775  .067202479   R-squared       =    0.0050
-------------+----------------------------------   Adj R-squared   =   -0.0015
       Total |  52.3411085       780  .067103985   Root MSE        =    .25923

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_immigra~n |  -.0064311   .0235032    -0.27   0.784    -.0525686    .0397064
      female |   .0274723   .0186739     1.47   0.142    -.0091851    .0641297
         age |  -.0005844   .0007345    -0.80   0.426    -.0020263    .0008574
      income |  -.0066955    .039718    -0.17   0.866    -.0846632    .0712722
  university |   .0140787   .0194351     0.72   0.469     -.024073    .0522304
       _cons |   .0385701   .0376604     1.02   0.306    -.0353584    .1124987
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_milspend female age income university  

      Source |       SS           df       MS      Number of obs   =       733
-------------+----------------------------------   F(5, 727)       =      1.16
       Model |  .376781408         5  .075356282   Prob &gt; F        =    0.3267
    Residual |   47.178777       727  .064895154   R-squared       =    0.0079
-------------+----------------------------------   Adj R-squared   =    0.0011
       Total |  47.5555584       732   .06496661   Root MSE        =    .25475

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 wp_milspend |  -.0292702   .0215725    -1.36   0.175     -.071622    .0130817
      female |   .0240563   .0189447     1.27   0.205    -.0131365    .0612492
         age |  -.0006531   .0007256    -0.90   0.368    -.0020776    .0007713
      income |   -.004753   .0397249    -0.12   0.905    -.0827422    .0732361
  university |   .0157217   .0195339     0.80   0.421    -.0226278    .0540712
       _cons |   .0534543   .0386881     1.38   0.167    -.0224995    .1294081
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_obedience female age income university  

      Source |       SS           df       MS      Number of obs   =       788
-------------+----------------------------------   F(5, 782)       =      0.88
       Model |  .291815772         5  .058363154   Prob &gt; F        =    0.4958
    Residual |  52.0293691       782   .06653372   R-squared       =    0.0056
-------------+----------------------------------   Adj R-squared   =   -0.0008
       Total |  52.3211849       787  .066481811   Root MSE        =    .25794

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_obedience |  -.0194714   .0224512    -0.87   0.386     -.063543    .0246003
      female |   .0284451   .0185099     1.54   0.125      -.00789    .0647801
         age |  -.0004972   .0007308    -0.68   0.496    -.0019318    .0009374
      income |  -.0033529   .0391639    -0.09   0.932    -.0802318     .073526
  university |   .0104501   .0193935     0.54   0.590    -.0276193    .0485195
       _cons |   .0440785    .038413     1.15   0.252    -.0313262    .1194833
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_patriotism female age income university  

      Source |       SS           df       MS      Number of obs   =       788
-------------+----------------------------------   F(5, 782)       =      0.97
       Model |  .321498422         5  .064299684   Prob &gt; F        =    0.4354
    Residual |  51.8567356       782  .066312961   R-squared       =    0.0062
-------------+----------------------------------   Adj R-squared   =   -0.0002
       Total |   52.178234       787   .06630017   Root MSE        =    .25751

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_patriot~m |  -.0212288   .0230688    -0.92   0.358     -.066513    .0240554
      female |   .0286829   .0184536     1.55   0.121    -.0075416    .0649074
         age |  -.0006301   .0007289    -0.86   0.388    -.0020608    .0008007
      income |  -.0097029    .039073    -0.25   0.804    -.0864033    .0669976
  university |    .011572   .0191771     0.60   0.546    -.0260726    .0492166
       _cons |   .0552679   .0406494     1.36   0.174    -.0245269    .1350628
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_pollution female age income university  

      Source |       SS           df       MS      Number of obs   =       789
-------------+----------------------------------   F(5, 783)       =      0.97
       Model |  .320618384         5  .064123677   Prob &gt; F        =    0.4382
    Residual |  52.0184621       783  .066434817   R-squared       =    0.0061
-------------+----------------------------------   Adj R-squared   =   -0.0002
       Total |  52.3390805       788  .066420153   Root MSE        =    .25775

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_pollution |   .0357278   .0350534     1.02   0.308    -.0330819    .1045375
      female |   .0275031   .0184587     1.49   0.137    -.0087312    .0637374
         age |    -.00055    .000729    -0.75   0.451    -.0019811    .0008811
      income |  -.0012303   .0390627    -0.03   0.975    -.0779104    .0754497
  university |   .0150146   .0191939     0.78   0.434     -.022663    .0526923
       _cons |   .0281056    .036632     0.77   0.443    -.0438031    .1000142
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_socialism female age income university  

      Source |       SS           df       MS      Number of obs   =       785
-------------+----------------------------------   F(5, 779)       =      1.29
       Model |  .429003548         5   .08580071   Prob &gt; F        =    0.2666
    Residual |  51.8590442       779  .066571302   R-squared       =    0.0082
-------------+----------------------------------   Adj R-squared   =    0.0018
       Total |  52.2880477       784  .066693938   Root MSE        =    .25801

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_socialism |   .0370367   .0225457     1.64   0.101    -.0072208    .0812942
      female |   .0299288   .0185707     1.61   0.107    -.0065257    .0663833
         age |  -.0006021     .00073    -0.82   0.410     -.002035    .0008309
      income |  -.0074319   .0391586    -0.19   0.850    -.0843008    .0694371
  university |   .0110792   .0192835     0.57   0.566    -.0267746    .0489331
       _cons |    .023354   .0372186     0.63   0.531    -.0497066    .0964145
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_taxcuts female age income university  

      Source |       SS           df       MS      Number of obs   =       785
-------------+----------------------------------   F(5, 779)       =      1.85
       Model |  .603453671         5  .120690734   Prob &gt; F        =    0.1011
    Residual |  50.8554685       779  .065283015   R-squared       =    0.0117
-------------+----------------------------------   Adj R-squared   =    0.0054
       Total |  51.4589221       784   .06563638   Root MSE        =    .25551

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  wp_taxcuts |   -.050794   .0218547    -2.32   0.020     -.093695    -.007893
      female |   .0251069   .0183435     1.37   0.171    -.0109016    .0611154
         age |   -.000808    .000726    -1.11   0.266    -.0022331    .0006172
      income |  -.0014091   .0388421    -0.04   0.971    -.0776567    .0748384
  university |   .0163039   .0190438     0.86   0.392    -.0210793    .0536871
       _cons |   .0746042   .0395512     1.89   0.060    -.0030354    .1522438
------------------------------------------------------------------------------
. regress mean_ph_dif3_all wp_women female age income university 

      Source |       SS           df       MS      Number of obs   =       789
-------------+----------------------------------   F(5, 783)       =      0.77
       Model |  .255365624         5  .051073125   Prob &gt; F        =    0.5737
    Residual |  52.1347449       783  .066583327   R-squared       =    0.0049
-------------+----------------------------------   Adj R-squared   =   -0.0015
       Total |  52.3901106       788  .066484912   Root MSE        =    .25804

------------------------------------------------------------------------------
mean_p~3_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    wp_women |  -.0159998    .037674    -0.42   0.671    -.0899539    .0579542
      female |   .0261525   .0185626     1.41   0.159    -.0102859    .0625908
         age |  -.0005576   .0007296    -0.76   0.445    -.0019899    .0008747
      income |  -.0052771   .0393065    -0.13   0.893    -.0824358    .0718816
  university |   .0132449   .0192326     0.69   0.491    -.0245087    .0509986
       _cons |   .0372489   .0367274     1.01   0.311    -.0348469    .1093446
------------------------------------------------------------------------------
.     
. regress mean_ph_dif2_all wp_right2 female age income university  

      Source |       SS           df       MS      Number of obs   =       796
-------------+----------------------------------   F(5, 790)       =      1.87
       Model |  .631060926         5  .126212185   Prob &gt; F        =    0.0971
    Residual |  53.3020628       790  .067470966   R-squared       =    0.0117
-------------+----------------------------------   Adj R-squared   =    0.0054
       Total |  53.9331237       795  .067840407   Root MSE        =    .25975

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   wp_right2 |  -.0531159   .0421163    -1.26   0.208    -.1357891    .0295573
      female |   .0417556   .0185246     2.25   0.024     .0053924    .0781189
         age |  -.0004022   .0007328    -0.55   0.583    -.0018406    .0010362
      income |  -.0588729   .0393908    -1.49   0.135    -.1361959    .0184501
  university |  -.0036823   .0193342    -0.19   0.849    -.0416349    .0342703
       _cons |   .0772974   .0411082     1.88   0.060    -.0033968    .1579916
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_abortion female age income university   

      Source |       SS           df       MS      Number of obs   =       791
-------------+----------------------------------   F(5, 785)       =      1.64
       Model |  .556306414         5  .111261283   Prob &gt; F        =    0.1477
    Residual |  53.3472081       785  .067958227   R-squared       =    0.0103
-------------+----------------------------------   Adj R-squared   =    0.0040
       Total |  53.9035145       790  .068232297   Root MSE        =    .26069

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 wp_abortion |   -.015364   .0217024    -0.71   0.479    -.0579656    .0272376
      female |   .0426767   .0186467     2.29   0.022     .0060734      .07928
         age |  -.0004301   .0007362    -0.58   0.559    -.0018753    .0010151
      income |   -.058121   .0396559    -1.47   0.143    -.1359651    .0197232
  university |  -.0017518   .0194553    -0.09   0.928    -.0399423    .0364387
       _cons |    .059711   .0379948     1.57   0.116    -.0148723    .1342944
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_capitalism female age income university  

      Source |       SS           df       MS      Number of obs   =       788
-------------+----------------------------------   F(5, 782)       =      1.60
       Model |  .546622987         5  .109324597   Prob &gt; F        =    0.1568
    Residual |  53.3288443       782  .068195453   R-squared       =    0.0101
-------------+----------------------------------   Adj R-squared   =    0.0038
       Total |  53.8754673       787  .068456756   Root MSE        =    .26114

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_capital~m |   .0136083   .0229182     0.59   0.553    -.0313802    .0585968
      female |   .0428814   .0187795     2.28   0.023     .0060172    .0797457
         age |  -.0004524   .0007367    -0.61   0.539    -.0018986    .0009938
      income |   -.061271   .0404117    -1.52   0.130    -.1405993    .0180572
  university |  -.0014578   .0194752    -0.07   0.940    -.0396877    .0367722
       _cons |   .0498354    .037848     1.32   0.188    -.0244604    .1241312
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_cencorship female age income university  

      Source |       SS           df       MS      Number of obs   =       786
-------------+----------------------------------   F(5, 780)       =      1.87
       Model |  .636103885         5  .127220777   Prob &gt; F        =    0.0978
    Residual |  53.1506995       780  .068141922   R-squared       =    0.0118
-------------+----------------------------------   Adj R-squared   =    0.0055
       Total |  53.7868034       785  .068518221   Root MSE        =    .26104

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_cencors~p |  -.0316561   .0219991    -1.44   0.151    -.0748405    .0115283
      female |   .0436812   .0187677     2.33   0.020       .00684    .0805224
         age |  -.0005252   .0007407    -0.71   0.479    -.0019791    .0009288
      income |  -.0604614   .0401079    -1.51   0.132    -.1391936    .0182707
  university |  -.0026489   .0195281    -0.14   0.892    -.0409827    .0356849
       _cons |   .0698827   .0390011     1.79   0.074    -.0066768    .1464422
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_deathp female age income university  

      Source |       SS           df       MS      Number of obs   =       789
-------------+----------------------------------   F(5, 783)       =      1.59
       Model |  .541442258         5  .108288452   Prob &gt; F        =    0.1602
    Residual |  53.3062697       783  .068079527   R-squared       =    0.0101
-------------+----------------------------------   Adj R-squared   =    0.0037
       Total |   53.847712       788   .06833466   Root MSE        =    .26092

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   wp_deathp |  -.0167181   .0212759    -0.79   0.432    -.0584826    .0250465
      female |   .0424557    .018691     2.27   0.023     .0057653     .079146
         age |   -.000469   .0007396    -0.63   0.526    -.0019209    .0009829
      income |  -.0573315   .0400076    -1.43   0.152    -.1358664    .0212034
  university |  -.0023309   .0194976    -0.12   0.905    -.0406047    .0359429
       _cons |   .0625196   .0390842     1.60   0.110    -.0142027    .1392419
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_gaymarriage female age income university  

      Source |       SS           df       MS      Number of obs   =       788
-------------+----------------------------------   F(5, 782)       =      1.88
       Model |  .636594435         5  .127318887   Prob &gt; F        =    0.0952
    Residual |  52.9138967       782   .06766483   R-squared       =    0.0119
-------------+----------------------------------   Adj R-squared   =    0.0056
       Total |  53.5504911       787  .068043826   Root MSE        =    .26012

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_gaymarr~e |  -.0294067   .0215678    -1.36   0.173    -.0717443    .0129308
      female |   .0416635   .0186696     2.23   0.026     .0050151    .0783119
         age |  -.0004074    .000736    -0.55   0.580    -.0018522    .0010374
      income |  -.0565654   .0399058    -1.42   0.157    -.1349006    .0217698
  university |  -.0034059   .0195273    -0.17   0.862    -.0417381    .0349264
       _cons |    .064564   .0380037     1.70   0.090    -.0100373    .1391653
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_guncontrol female age income university  

      Source |       SS           df       MS      Number of obs   =       790
-------------+----------------------------------   F(5, 784)       =      1.76
       Model |  .598561437         5  .119712287   Prob &gt; F        =    0.1185
    Residual |  53.3032285       784  .067988812   R-squared       =    0.0111
-------------+----------------------------------   Adj R-squared   =    0.0048
       Total |  53.9017899       789   .06831659   Root MSE        =    .26075

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_guncont~l |  -.0305017   .0284785    -1.07   0.284    -.0864049    .0254015
      female |      .0417    .018671     2.23   0.026      .005049     .078351
         age |   -.000458   .0007366    -0.62   0.534     -.001904     .000988
      income |  -.0561215   .0395388    -1.42   0.156     -.133736     .021493
  university |  -.0014944    .019424    -0.08   0.939    -.0396235    .0366348
       _cons |   .0591168   .0371452     1.59   0.112    -.0137989    .1320326
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_immigration female age income university  

      Source |       SS           df       MS      Number of obs   =       782
-------------+----------------------------------   F(5, 776)       =      1.43
       Model |  .489531034         5  .097906207   Prob &gt; F        =    0.2126
    Residual |  53.2910221       776  .068673998   R-squared       =    0.0091
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  53.7805531       781  .068861144   Root MSE        =    .26206

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_immigra~n |  -.0008105   .0237128    -0.03   0.973    -.0473593    .0457384
      female |   .0417486   .0188623     2.21   0.027     .0047213    .0787759
         age |  -.0004077   .0007421    -0.55   0.583    -.0018644    .0010489
      income |  -.0528861    .040153    -1.32   0.188    -.1317074    .0259353
  university |  -.0010141   .0196418    -0.05   0.959    -.0395715    .0375432
       _cons |   .0518713   .0379945     1.37   0.173    -.0227129    .1264555
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_milspend female age income university  

      Source |       SS           df       MS      Number of obs   =       734
-------------+----------------------------------   F(5, 728)       =      1.21
       Model |  .395024937         5  .079004987   Prob &gt; F        =    0.3015
    Residual |  47.4409971       728  .065166205   R-squared       =    0.0083
-------------+----------------------------------   Adj R-squared   =    0.0014
       Total |   47.836022       733  .065260603   Root MSE        =    .25528

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 wp_milspend |  -.0119269   .0216118    -0.55   0.581    -.0543558    .0305019
      female |   .0337258   .0189707     1.78   0.076     -.003518    .0709696
         age |  -.0005291   .0007266    -0.73   0.467    -.0019556    .0008974
      income |  -.0520886   .0398206    -1.31   0.191    -.1302655    .0260882
  university |  -.0060779   .0195623    -0.31   0.756    -.0444831    .0323273
       _cons |   .0684259   .0387381     1.77   0.078    -.0076257    .1444776
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_obedience female age income university  

      Source |       SS           df       MS      Number of obs   =       789
-------------+----------------------------------   F(5, 783)       =      1.64
       Model |  .557661539         5  .111532308   Prob &gt; F        =    0.1476
    Residual |  53.3362121       783  .068117768   R-squared       =    0.0103
-------------+----------------------------------   Adj R-squared   =    0.0040
       Total |  53.8938737       788  .068393241   Root MSE        =    .26099

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_obedience |  -.0152776   .0226769    -0.67   0.501    -.0597923     .029237
      female |   .0436527   .0187165     2.33   0.020     .0069123    .0803931
         age |  -.0004026   .0007392    -0.54   0.586    -.0018537    .0010484
      income |  -.0543833   .0396375    -1.37   0.170    -.1321916     .023425
  university |  -.0024141   .0196021    -0.12   0.902    -.0408929    .0360647
       _cons |    .060264   .0387522     1.56   0.120    -.0158065    .1363344
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_patriotism female age income university  

      Source |       SS           df       MS      Number of obs   =       789
-------------+----------------------------------   F(5, 783)       =      1.64
       Model |  .558441319         5  .111688264   Prob &gt; F        =    0.1464
    Residual |   53.254015       783   .06801279   R-squared       =    0.0104
-------------+----------------------------------   Adj R-squared   =    0.0041
       Total |  53.8124563       788  .068289919   Root MSE        =    .26079

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_patriot~m |   .0008803   .0232879     0.04   0.970    -.0448338    .0465944
      female |   .0434073   .0186779     2.32   0.020     .0067426    .0800721
         age |  -.0004447   .0007377    -0.60   0.547    -.0018928    .0010035
      income |  -.0594799   .0395889    -1.50   0.133    -.1371928     .018233
  university |  -.0015349   .0194154    -0.08   0.937    -.0396473    .0365775
       _cons |   .0551897   .0411288     1.34   0.180    -.0255461    .1359255
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_pollution female age income university  

      Source |       SS           df       MS      Number of obs   =       790
-------------+----------------------------------   F(5, 784)       =      1.53
       Model |  .521378521         5  .104275704   Prob &gt; F        =    0.1775
    Residual |  53.3805452       784   .06808743   R-squared       =    0.0097
-------------+----------------------------------   Adj R-squared   =    0.0034
       Total |  53.9019238       789   .06831676   Root MSE        =    .26094

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_pollution |   .0005518   .0354859     0.02   0.988    -.0691068    .0702105
      female |    .042331   .0186752     2.27   0.024     .0056716    .0789903
         age |  -.0004395   .0007376    -0.60   0.551    -.0018874    .0010084
      income |  -.0550388   .0395602    -1.39   0.165    -.1326951    .0226176
  university |  -.0005929   .0194252    -0.03   0.976    -.0387244    .0375386
       _cons |   .0527284   .0370501     1.42   0.155    -.0200008    .1254576
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_socialism female age income university  

      Source |       SS           df       MS      Number of obs   =       786
-------------+----------------------------------   F(5, 780)       =      1.80
       Model |  .612855747         5  .122571149   Prob &gt; F        =    0.1113
    Residual |  53.2475868       780  .068266137   R-squared       =    0.0114
-------------+----------------------------------   Adj R-squared   =    0.0050
       Total |  53.8604425       785  .068612029   Root MSE        =    .26128

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
wp_socialism |  -.0273926   .0228201    -1.20   0.230    -.0721887    .0174035
      female |   .0403175   .0187942     2.15   0.032     .0034244    .0772106
         age |   -.000454   .0007387    -0.61   0.539    -.0019041    .0009962
      income |  -.0532732   .0396608    -1.34   0.180    -.1311278    .0245814
  university |  -.0002687   .0195164    -0.01   0.989    -.0385797    .0380422
       _cons |   .0635406   .0376984     1.69   0.092    -.0104617    .1375429
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_taxcuts female age income university  

      Source |       SS           df       MS      Number of obs   =       786
-------------+----------------------------------   F(5, 780)       =      1.94
       Model |  .659711326         5  .131942265   Prob &gt; F        =    0.0856
    Residual |  53.0577564       780  .068022765   R-squared       =    0.0123
-------------+----------------------------------   Adj R-squared   =    0.0059
       Total |  53.7174678       785  .068429895   Root MSE        =    .26081

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  wp_taxcuts |  -.0294665   .0222994    -1.32   0.187    -.0732404    .0143073
      female |   .0440057   .0187128     2.35   0.019     .0072723    .0807391
         age |  -.0005342   .0007406    -0.72   0.471    -.0019881    .0009197
      income |  -.0549325   .0396607    -1.39   0.166    -.1327868    .0229218
  university |   .0004892   .0194326     0.03   0.980    -.0376573    .0386357
       _cons |   .0737054   .0403231     1.83   0.068    -.0054493    .1528601
------------------------------------------------------------------------------
. regress mean_ph_dif2_all wp_women female age income university 

      Source |       SS           df       MS      Number of obs   =       790
-------------+----------------------------------   F(5, 784)       =      1.65
       Model |  .560102296         5  .112020459   Prob &gt; F        =    0.1453
    Residual |  53.3439947       784   .06804081   R-squared       =    0.0104
-------------+----------------------------------   Adj R-squared   =    0.0041
       Total |   53.904097       789  .068319515   Root MSE        =    .26085

------------------------------------------------------------------------------
mean_p~2_all |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    wp_women |   .0288333   .0380835     0.76   0.449    -.0459245     .103591
      female |   .0439023   .0187528     2.34   0.019     .0070907    .0807139
         age |  -.0004559   .0007371    -0.62   0.536    -.0019029    .0009911
      income |  -.0529817   .0397485    -1.33   0.183    -.1310078    .0250443
  university |   .0003343   .0194353     0.02   0.986    -.0378171    .0384857
       _cons |   .0485386   .0370904     1.31   0.191    -.0242697     .121347
------------------------------------------------------------------------------
.         
.                              
.   
. * Table A8 Row 1
. quietly regress mean_dif2 wp_right2 female age income university 
. estimates store A
. quietly regress mean_dif2 wp_right2 female age income university if wp_right2
&gt; _ext==1
. estimates store B
. quietly regress mean_dif2 wp_right2 female age income university if political
&gt; _interest_dichox==1
. estimates store C
. esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)

------------------------------------------------------------
                      (1)             (2)             (3)   
                mean_dif2       mean_dif2       mean_dif2   
                     b/se            b/se            b/se   
------------------------------------------------------------
wp_right2           0.104           0.206           0.323** 
                  (0.093)         (0.111)         (0.121)   
female             -0.023          -0.050          -0.071   
                  (0.042)         (0.060)         (0.060)   
age                -0.003          -0.003          -0.002   
                  (0.002)         (0.003)         (0.002)   
income              0.086           0.120           0.032   
                  (0.088)         (0.122)         (0.125)   
university         -0.054          -0.021           0.003   
                  (0.044)         (0.064)         (0.067)   
_cons               0.131           0.033          -0.022   
                  (0.093)         (0.128)         (0.130)   
------------------------------------------------------------
r2                  0.007           0.012           0.020   
r2_a                0.002           0.002           0.009   
N                 933.000         505.000         444.000   
------------------------------------------------------------
. regress mean_dif2 wp_right2 female age income university if political_interes
&gt; t_dichox==1, beta

      Source |       SS           df       MS      Number of obs   =       444
-------------+----------------------------------   F(5, 438)       =      1.78
       Model |  3.33233263         5  .666466526   Prob &gt; F        =    0.1162
    Residual |  164.257414       438  .375016928   R-squared       =    0.0199
-------------+----------------------------------   Adj R-squared   =    0.0087
       Total |  167.589747       443  .378306427   Root MSE        =    .61239

------------------------------------------------------------------------------
   mean_dif2 |      Coef.   Std. Err.      t    P&gt;|t|                     Beta
-------------+----------------------------------------------------------------
   wp_right2 |   .3233054    .121261     2.67   0.008                 .1276749
      female |  -.0709586   .0596313    -1.19   0.235                -.0570675
         age |  -.0015231   .0024292    -0.63   0.531                -.0301753
      income |   .0323931   .1253699     0.26   0.796                 .0122521
  university |   .0026998   .0667772     0.04   0.968                 .0019359
       _cons |  -.0221748    .130452    -0.17   0.865                        .
------------------------------------------------------------------------------
. regress md2 wp2 female age income university if political_interest_dichox==1

      Source |       SS           df       MS      Number of obs   =       444
-------------+----------------------------------   F(5, 438)       =      1.78
       Model |  8.34174647         5  1.66834929   Prob &gt; F        =    0.1162
    Residual |   411.18152       438  .938770593   R-squared       =    0.0199
-------------+----------------------------------   Adj R-squared   =    0.0087
       Total |  419.523266       443  .947005115   Root MSE        =     .9689

------------------------------------------------------------------------------
         md2 |      Coef.   Std. Err.      t    P&gt;|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         wp2 |   .1154357    .043296     2.67   0.008     .0303419    .2005295
      female |  -.1122688   .0943471    -1.19   0.235    -.2976982    .0731605
         age |  -.0024098   .0038434    -0.63   0.531    -.0099636     .005144
      income |   .0512515    .198357     0.26   0.796    -.3385983    .4411012
  university |   .0042716   .1056531     0.04   0.968    -.2033785    .2119217
       _cons |   .0404929   .1913442     0.21   0.832     -.335574    .4165599
------------------------------------------------------------------------------
. * Table A8 Row 4
. quietly regress mean_ph_dif_all wp_right2 female age income university  
. estimates store A
. quietly regress mean_ph_dif_all wp_right2 female age income university if wp_
&gt; right2_ext==1
. estimates store B
. quietly regress mean_ph_dif_all wp_right2 female age income university if pol
&gt; itical_interest_dichox==1
. estimates store C
. esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2 r2_a N)

------------------------------------------------------------
                      (1)             (2)             (3)   
             mean_p~f_all    mean_p~f_all    mean_p~f_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
wp_right2          -0.069*         -0.053          -0.082   
                  (0.034)         (0.040)         (0.045)   
female              0.031*          0.071***        0.022   
                  (0.015)         (0.021)         (0.022)   
age                -0.000           0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
income             -0.026          -0.014           0.010   
                  (0.032)         (0.044)         (0.046)   
university          0.002          -0.001           0.002   
                  (0.016)         (0.023)         (0.024)   
_cons               0.073*          0.005           0.044   
                  (0.033)         (0.046)         (0.047)   
------------------------------------------------------------
r2                  0.013           0.029           0.012   
r2_a                0.007           0.018          -0.002   
N                 806.000         432.000         377.000   
------------------------------------------------------------
.       
.     </code></pre>
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</div>
<div id="analysis-of-stimulus-data.dta" class="section level2">
<h2>Analysis of Stimulus-data.dta</h2>
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<pre class="r"><code>
coefs &lt;- as.data.frame(countries)
coefs$b &lt;- NA
coefs$se &lt;- NA
E &lt;- R[R$stimtype==&quot;single video&quot; &amp; R$local==0,]
E &lt;- E[!is.na(E$vid_order),]
E$negativity &lt;- E$v_negativity
Pd &lt;- pdata.frame(E,index = c(&quot;resp&quot;, &quot;vid_order&quot;))
Pd$orderN &lt;- as.numeric(Pd$vid_order)
for (i in countries){
  model &lt;- plm(gslmc ~ negativity * wp_right2 + orderN + female + age + income + university,
               data=Pd[Pd$country2==i,], model=&quot;random&quot;)
  s &lt;- summary(model)$coef
  coefs$b[coefs$countries==i] &lt;- s[9,1]
  coefs$se[coefs$countries==i] &lt;- s[9,2]
}
coefs$low &lt;- coefs$b - (coefs$se * 1.96)
coefs$high &lt;- coefs$b + (coefs$se * 1.96)
coefs$range &lt;- as.numeric(rownames(coefs))

{
pdf(&quot;figure3.pdf&quot;, width = 10, height = 5, bg=&quot;white&quot;) 
par(mar=c(5.1,4.1,1.1,2.1))
plot(coefs$range,coefs$b,type=&quot;n&quot;,ann=F,axes=F,ylim=c(-1.5,1.5))
abline(h=0,lwd=1,lty=2,col=&quot;black&quot;)
arrows(coefs$range,coefs$low,coefs$range,coefs$high,angle=90,length=.05,code=3,col=&quot;gray&quot;,lwd=2,lty=1)
points(coefs$range,coefs$b,pch=15,cex=1.5)
axis(1,col=&quot;white&quot;,at=c(1:19),labels=coefs$countries,cex.axis=.8)
axis(2,las=1)
mtext(&quot;Ideological Difference in the Effect of Negativity&quot;,side=2,line=3)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
stata_src &lt;- readLines(&quot;Stimulus-data.do&quot;)
stata(stata_src,data.in=R)</code></pre>
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<!-- rnb-output-begin {"data":". *** Syntax for analyses of stimulus-level data\n. *** Use data file 'Stimulus-data.dta' with this syntax\n. * Table 3\n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(39,228 real changes made)\n.   quietly xtreg gslmc neg vid_order female age income university if stimtype=\n> =\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc neg vid_order female age income university if wp_right2\n> _dichox==0 & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc neg vid_order female age income university if wp_right2\n> _dichox==1 & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 , re \n.   estimates store G  \n.   esttab D E F G , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b\n>  r2_o N N_g)\n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.034**         0.028           0.041**         0.017   \n                  (0.011)         (0.016)         (0.015)         (0.022)   \nvid_order          -0.074***       -0.077***       -0.070***       -0.074***\n                  (0.005)         (0.007)         (0.007)         (0.005)   \nfemale             -0.028          -0.032          -0.020          -0.027   \n                  (0.023)         (0.034)         (0.032)         (0.023)   \nage                 0.001           0.001           0.001           0.001   \n                  (0.001)         (0.002)         (0.001)         (0.001)   \nincome              0.013           0.028          -0.006           0.016   \n                  (0.049)         (0.069)         (0.070)         (0.049)   \nuniversity         -0.026          -0.058           0.009          -0.021   \n                  (0.024)         (0.036)         (0.034)         (0.025)   \nwp_right2                                                           0.063   \n                                                                  (0.052)   \nc.neg#c.wp~2                                                        0.045   \n                                                                  (0.048)   \n_cons               0.243***        0.251***        0.234**         0.215***\n                  (0.051)         (0.073)         (0.071)         (0.055)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.049           0.051           0.050   \nr2_b                0.035           0.041           0.031           0.037   \nr2_o                0.045           0.047           0.045           0.046   \nN                4665.000        2355.000        2310.000        4665.000   \nN_g               933.000         471.000         462.000         933.000   \n----------------------------------------------------------------------------\n.       \n. * Figure 3\n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.036          -0.112          -0.078   \n                  (0.139)         (0.101)         (0.061)   \nwp_right2          -0.275          -0.112          -0.268   \n                  (0.325)         (0.571)         (0.203)   \nc.neg#c.wp~2        0.140           0.731*          0.134   \n                  (0.338)         (0.341)         (0.188)   \nvid_order          -0.071*         -0.122***       -0.042*  \n                  (0.030)         (0.030)         (0.019)   \nfemale             -0.083           0.188          -0.013   \n                  (0.122)         (0.249)         (0.101)   \nage                 0.013           0.025          -0.002   \n                  (0.012)         (0.025)         (0.003)   \nincome              0.021          -0.201           0.050   \n                  (0.281)         (0.443)         (0.197)   \nuniversity         -0.016          -0.167          -0.061   \n                  (0.129)         (0.336)         (0.105)   \n_cons               0.097          -0.176           0.326   \n                  (0.349)         (0.779)         (0.228)   \n------------------------------------------------------------\nr2_w                0.048           0.152           0.059   \nr2_b                0.121           0.085           0.077   \nr2_o                0.057           0.129           0.063   \nN                 175.000         160.000         135.000   \nN_g                35.000          32.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.104          -0.086          -0.082   \n                  (0.120)         (0.186)         (0.082)   \nwp_right2           0.445          -0.112           0.067   \n                  (0.481)         (0.383)         (0.252)   \nc.neg#c.wp~2       -0.110           0.224           0.342   \n                  (0.329)         (0.361)         (0.239)   \nvid_order          -0.108***       -0.111***       -0.041*  \n                  (0.029)         (0.023)         (0.019)   \nfemale              0.170           0.006          -0.008   \n                  (0.172)         (0.105)         (0.086)   \nage                 0.005          -0.011           0.001   \n                  (0.007)         (0.010)         (0.003)   \nincome              0.100           0.429           0.252   \n                  (0.497)         (0.257)         (0.184)   \nuniversity          0.229          -0.133          -0.009   \n                  (0.176)         (0.153)         (0.085)   \n_cons              -0.341           0.668          -0.044   \n                  (0.426)         (0.355)         (0.200)   \n------------------------------------------------------------\nr2_w                0.099           0.094           0.042   \nr2_b                0.129           0.130           0.163   \nr2_o                0.108           0.099           0.057   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.068           0.153           0.109   \n                  (0.125)         (0.097)         (0.110)   \nwp_right2          -0.090          -0.077          -0.236   \n                  (0.394)         (0.161)         (0.209)   \nc.neg#c.wp~2        0.077          -0.205          -0.176   \n                  (0.311)         (0.149)         (0.172)   \nvid_order          -0.119***       -0.067***       -0.087***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.106          -0.124*         -0.110   \n                  (0.128)         (0.055)         (0.084)   \nage                -0.003           0.001           0.002   \n                  (0.007)         (0.003)         (0.006)   \nincome              0.029           0.156           0.117   \n                  (0.310)         (0.108)         (0.176)   \nuniversity         -0.077          -0.033          -0.101   \n                  (0.129)         (0.057)         (0.098)   \n_cons               0.708*          0.243           0.363   \n                  (0.332)         (0.145)         (0.219)   \n------------------------------------------------------------\nr2_w                0.106           0.109           0.101   \nr2_b                0.055           0.202           0.185   \nr2_o                0.095           0.131           0.120   \nN                 255.000         300.000         250.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.071           0.006           0.040   \n                  (0.088)         (0.161)         (0.057)   \nwp_right2           0.241          -0.379           0.070   \n                  (0.406)         (0.391)         (0.251)   \nc.neg#c.wp~2        0.220           0.194          -0.049   \n                  (0.309)         (0.402)         (0.200)   \nvid_order          -0.133***       -0.048          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.100           0.112          -0.178*  \n                  (0.132)         (0.152)         (0.082)   \nage                -0.011           0.010           0.001   \n                  (0.023)         (0.039)         (0.007)   \nincome             -0.392          -0.043           0.451*  \n                  (0.300)         (0.377)         (0.228)   \nuniversity         -0.254          -0.100           0.167   \n                  (0.188)         (0.292)         (0.124)   \n_cons               1.094           0.098          -0.090   \n                  (0.684)         (0.867)         (0.304)   \n------------------------------------------------------------\nr2_w                0.075           0.016           0.101   \nr2_b                0.154           0.163           0.205   \nr2_o                0.095           0.035           0.129   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b\n>  r2_o N N_g)\n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.063          -0.060           0.082          -0.097   \n                  (0.170)         (0.080)         (0.152)         (0.069)   \nwp_right2           0.139           0.236           0.283           0.017   \n                  (0.484)         (0.246)         (0.252)         (0.137)   \nc.neg#c.wp~2       -0.004           0.208          -0.067           0.160   \n                  (0.445)         (0.211)         (0.252)         (0.112)   \nvid_order          -0.099**        -0.087***       -0.062*         -0.020*  \n                  (0.034)         (0.021)         (0.026)         (0.009)   \nfemale              0.073          -0.090           0.110          -0.008   \n                  (0.150)         (0.102)         (0.104)         (0.048)   \nage                -0.046          -0.004           0.005           0.003   \n                  (0.049)         (0.002)         (0.005)         (0.002)   \nincome             -0.389           0.094          -0.058           0.210   \n                  (0.291)         (0.160)         (0.263)         (0.146)   \nuniversity         -0.055           0.012          -0.075           0.015   \n                  (0.233)         (0.098)         (0.159)         (0.048)   \n_cons               1.526           0.390*         -0.066          -0.091   \n                  (1.120)         (0.195)         (0.311)         (0.134)   \n----------------------------------------------------------------------------\nr2_w                0.052           0.108           0.042           0.023   \nr2_b                0.189           0.331           0.225           0.112   \nr2_o                0.075           0.144           0.073           0.044   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.101          -0.012           0.051   \n                  (0.068)         (0.082)         (0.056)   \nwp_right2           0.108           0.012           0.125   \n                  (0.184)         (0.302)         (0.157)   \nc.neg#c.wp~2        0.198           0.274           0.005   \n                  (0.173)         (0.235)         (0.132)   \nvid_order          -0.025          -0.077***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.094          -0.097          -0.033   \n                  (0.085)         (0.110)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.425          -0.094          -0.010   \n                  (0.217)         (0.220)         (0.120)   \nuniversity          0.051          -0.054           0.078   \n                  (0.087)         (0.149)         (0.062)   \n_cons               0.161           0.480*         -0.006   \n                  (0.195)         (0.225)         (0.141)   \n------------------------------------------------------------\nr2_w                0.028           0.086           0.020   \nr2_b                0.219           0.058           0.026   \nr2_o                0.068           0.078           0.022   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.      \n.           \n. * Table 5 Columns 2 , 3 and 4\n.  \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(56,936 real changes made, 39,228 to missing)\n.   quietly xtreg p_gslmc_all neg pho_order female age income university if wp_\n> right2_dichox==0 & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all neg pho_order female age income university if wp_\n> right2_dichox==1 & stimtype==\"single photo\" , re \n.   estimates store C\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" , re \n.   estimates store D\n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.007**         0.013***\n                  (0.002)         (0.002)         (0.003)   \npho_order           0.002**         0.002**         0.002***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.010           0.013           0.012   \n                  (0.010)         (0.010)         (0.007)   \nage                -0.001          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.009          -0.024          -0.018   \n                  (0.022)         (0.021)         (0.015)   \nuniversity         -0.002           0.014           0.006   \n                  (0.011)         (0.010)         (0.007)   \nwp_right2                                           0.050   \n                                                  (0.037)   \nc.neg#c.wp~2                                       -0.012   \n                                                  (0.007)   \n_cons              -0.040          -0.059*         -0.070** \n                  (0.025)         (0.024)         (0.023)   \n------------------------------------------------------------\nr2_w                0.003           0.003           0.003   \nr2_b                0.019           0.016           0.015   \nr2_o                0.004           0.003           0.003   \nN                7783.000        7480.000       15263.000   \nN_g               410.000         394.000         804.000   \n------------------------------------------------------------\n.   \n. * Table 6 Column 1\n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H  \n.   esttab B D E , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.006           0.007          -0.003   \n                  (0.017)         (0.013)         (0.016)   \nwp_right2          -0.105           0.009          -0.288   \n                  (0.214)         (0.220)         (0.230)   \nc.neg#c.wp~2        0.011           0.015           0.037   \n                  (0.042)         (0.040)         (0.044)   \npho_order           0.005*          0.006*          0.002   \n                  (0.002)         (0.003)         (0.003)   \nfemale             -0.023           0.070           0.031   \n                  (0.037)         (0.061)         (0.040)   \nage                -0.002           0.000          -0.001   \n                  (0.004)         (0.002)         (0.002)   \nincome             -0.087          -0.145          -0.005   \n                  (0.079)         (0.118)         (0.115)   \nuniversity          0.015           0.121          -0.051   \n                  (0.037)         (0.063)         (0.041)   \n_cons               0.008          -0.178           0.073   \n                  (0.131)         (0.142)         (0.125)   \n------------------------------------------------------------\nr2_w                0.013           0.014           0.003   \nr2_b                0.178           0.232           0.155   \nr2_o                0.018           0.032           0.008   \nN                 623.000         513.000         684.000   \nN_g                33.000          27.000          36.000   \n------------------------------------------------------------\n.   esttab F G H , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.009           0.007           0.030*  \n                  (0.027)         (0.009)         (0.015)   \nwp_right2          -0.071          -0.026           0.212   \n                  (0.274)         (0.145)         (0.197)   \nc.neg#c.wp~2        0.030          -0.004          -0.029   \n                  (0.052)         (0.026)         (0.038)   \npho_order           0.002           0.003*          0.005*  \n                  (0.003)         (0.001)         (0.002)   \nfemale              0.039          -0.067*          0.018   \n                  (0.036)         (0.028)         (0.030)   \nage                 0.001          -0.000           0.000   \n                  (0.003)         (0.001)         (0.002)   \nincome              0.013           0.036          -0.046   \n                  (0.095)         (0.060)         (0.074)   \nuniversity          0.012          -0.013           0.072*  \n                  (0.053)         (0.028)         (0.030)   \n_cons              -0.070          -0.060          -0.283** \n                  (0.174)         (0.075)         (0.106)   \n------------------------------------------------------------\nr2_w                0.002           0.012           0.016   \nr2_b                0.056           0.192           0.267   \nr2_o                0.004           0.027           0.024   \nN                1045.000         665.000         969.000   \nN_g                55.000          35.000          51.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab I J K , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014           0.005           0.012   \n                  (0.015)         (0.017)         (0.013)   \nwp_right2           0.020           0.061           0.322   \n                  (0.124)         (0.136)         (0.205)   \nc.neg#c.wp~2       -0.015          -0.015          -0.041   \n                  (0.023)         (0.026)         (0.037)   \npho_order           0.003*          0.001           0.001   \n                  (0.001)         (0.002)         (0.002)   \nfemale              0.020           0.026           0.004   \n                  (0.022)         (0.025)         (0.039)   \nage                -0.000          -0.001           0.002   \n                  (0.001)         (0.002)         (0.005)   \nincome             -0.025          -0.029          -0.029   \n                  (0.043)         (0.055)         (0.078)   \nuniversity         -0.022           0.020           0.007   \n                  (0.023)         (0.029)         (0.055)   \n_cons              -0.045          -0.014          -0.143   \n                  (0.090)         (0.104)         (0.173)   \n------------------------------------------------------------\nr2_w                0.006           0.002           0.003   \nr2_b                0.073           0.064           0.115   \nr2_o                0.011           0.004           0.008   \nN                1140.000         911.000         456.000   \nN_g                60.000          48.000          24.000   \n------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.037           0.008           0.027   \n                  (0.019)         (0.010)         (0.026)   \nwp_right2          -0.385           0.020           0.061   \n                  (0.247)         (0.178)         (0.359)   \nc.neg#c.wp~2        0.072          -0.012          -0.015   \n                  (0.048)         (0.035)         (0.068)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.032          -0.032           0.019   \n                  (0.044)         (0.026)         (0.054)   \nage                 0.005          -0.002           0.014   \n                  (0.011)         (0.002)         (0.018)   \nincome             -0.145           0.120           0.058   \n                  (0.106)         (0.072)         (0.105)   \nuniversity          0.133          -0.004          -0.105   \n                  (0.119)         (0.039)         (0.085)   \n_cons              -0.064          -0.048          -0.282   \n                  (0.266)         (0.107)         (0.423)   \n------------------------------------------------------------\nr2_w                0.017           0.011           0.007   \nr2_b                0.212           0.124           0.095   \nr2_o                0.030           0.017           0.010   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.046***        0.057**        -0.009   \n                  (0.013)         (0.019)         (0.011)   \nwp_right2           0.201           0.402*         -0.093   \n                  (0.191)         (0.164)         (0.088)   \nc.neg#c.wp~2       -0.077*         -0.072*          0.019   \n                  (0.035)         (0.032)         (0.017)   \npho_order           0.001          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.003          -0.014           0.016   \n                  (0.043)         (0.032)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.001          -0.061          -0.037   \n                  (0.068)         (0.080)         (0.043)   \nuniversity         -0.013          -0.036           0.001   \n                  (0.041)         (0.048)         (0.014)   \n_cons              -0.133          -0.170           0.056   \n                  (0.102)         (0.127)         (0.064)   \n------------------------------------------------------------\nr2_w                0.025           0.018           0.004   \nr2_b                0.163           0.136           0.108   \nr2_o                0.033           0.022           0.006   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009           0.009           0.016   \n                  (0.011)         (0.012)         (0.011)   \nwp_right2          -0.104           0.046           0.100   \n                  (0.152)         (0.178)         (0.142)   \nc.neg#c.wp~2        0.015          -0.018          -0.019   \n                  (0.029)         (0.034)         (0.028)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.059           0.053           0.005   \n                  (0.032)         (0.030)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.012          -0.078           0.045   \n                  (0.082)         (0.061)         (0.045)   \nuniversity          0.022          -0.053           0.021   \n                  (0.033)         (0.041)         (0.023)   \n_cons              -0.154           0.010          -0.090   \n                  (0.090)         (0.087)         (0.072)   \n------------------------------------------------------------\nr2_w                0.009           0.002           0.002   \nr2_b                0.193           0.152           0.033   \nr2_o                0.020           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.         \n. * Table A3 Row 2\n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(56,936 real changes made, 17,708 to missing)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 , re \n.   estimates store A    \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==1 , re \n.   estimates store B \n.   esttab A B , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2_\n> o N N_g)\n\n--------------------------------------------\n                      (1)             (2)   \n                    gslmc           gslmc   \n                     b/se            b/se   \n--------------------------------------------\nneg                 0.017           0.023   \n                  (0.022)         (0.032)   \nwp_right2           0.063          -0.108   \n                  (0.052)         (0.077)   \nc.neg#c.wp~2        0.045          -0.078   \n                  (0.048)         (0.068)   \nvid_order          -0.074***       -0.078***\n                  (0.005)         (0.008)   \nfemale             -0.027          -0.011   \n                  (0.023)         (0.034)   \nage                 0.001           0.001   \n                  (0.001)         (0.001)   \nincome              0.016          -0.001   \n                  (0.049)         (0.072)   \nuniversity         -0.021          -0.054   \n                  (0.025)         (0.036)   \n_cons               0.215***        0.327***\n                  (0.055)         (0.083)   \n--------------------------------------------\nr2_w                0.050           0.079   \nr2_b                0.037           0.022   \nr2_o                0.046           0.048   \nN                4665.000        1866.000   \nN_g               933.000         933.000   \n--------------------------------------------\n.    \n.    \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b\n>  r2_o N N_g)\n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.017          -0.036          -0.112          -0.078   \n                  (0.022)         (0.139)         (0.101)         (0.061)   \nwp_right2           0.063          -0.275          -0.112          -0.268   \n                  (0.052)         (0.325)         (0.571)         (0.203)   \nc.neg#c.wp~2        0.045           0.140           0.731*          0.134   \n                  (0.048)         (0.338)         (0.341)         (0.188)   \nvid_order          -0.074***       -0.071*         -0.122***       -0.042*  \n                  (0.005)         (0.030)         (0.030)         (0.019)   \nfemale             -0.027          -0.083           0.188          -0.013   \n                  (0.023)         (0.122)         (0.249)         (0.101)   \nage                 0.001           0.013           0.025          -0.002   \n                  (0.001)         (0.012)         (0.025)         (0.003)   \nincome              0.016           0.021          -0.201           0.050   \n                  (0.049)         (0.281)         (0.443)         (0.197)   \nuniversity         -0.021          -0.016          -0.167          -0.061   \n                  (0.025)         (0.129)         (0.336)         (0.105)   \n_cons               0.215***        0.097          -0.176           0.326   \n                  (0.055)         (0.349)         (0.779)         (0.228)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.048           0.152           0.059   \nr2_b                0.037           0.121           0.085           0.077   \nr2_o                0.046           0.057           0.129           0.063   \nN                4665.000         175.000         160.000         135.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.104          -0.086          -0.082   \n                  (0.120)         (0.186)         (0.082)   \nwp_right2           0.445          -0.112           0.067   \n                  (0.481)         (0.383)         (0.252)   \nc.neg#c.wp~2       -0.110           0.224           0.342   \n                  (0.329)         (0.361)         (0.239)   \nvid_order          -0.108***       -0.111***       -0.041*  \n                  (0.029)         (0.023)         (0.019)   \nfemale              0.170           0.006          -0.008   \n                  (0.172)         (0.105)         (0.086)   \nage                 0.005          -0.011           0.001   \n                  (0.007)         (0.010)         (0.003)   \nincome              0.100           0.429           0.252   \n                  (0.497)         (0.257)         (0.184)   \nuniversity          0.229          -0.133          -0.009   \n                  (0.176)         (0.153)         (0.085)   \n_cons              -0.341           0.668          -0.044   \n                  (0.426)         (0.355)         (0.200)   \n------------------------------------------------------------\nr2_w                0.099           0.094           0.042   \nr2_b                0.129           0.130           0.163   \nr2_o                0.108           0.099           0.057   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.068           0.153           0.109   \n                  (0.125)         (0.097)         (0.110)   \nwp_right2          -0.090          -0.077          -0.236   \n                  (0.394)         (0.161)         (0.209)   \nc.neg#c.wp~2        0.077          -0.205          -0.176   \n                  (0.311)         (0.149)         (0.172)   \nvid_order          -0.119***       -0.067***       -0.087***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.106          -0.124*         -0.110   \n                  (0.128)         (0.055)         (0.084)   \nage                -0.003           0.001           0.002   \n                  (0.007)         (0.003)         (0.006)   \nincome              0.029           0.156           0.117   \n                  (0.310)         (0.108)         (0.176)   \nuniversity         -0.077          -0.033          -0.101   \n                  (0.129)         (0.057)         (0.098)   \n_cons               0.708*          0.243           0.363   \n                  (0.332)         (0.145)         (0.219)   \n------------------------------------------------------------\nr2_w                0.106           0.109           0.101   \nr2_b                0.055           0.202           0.185   \nr2_o                0.095           0.131           0.120   \nN                 255.000         300.000         250.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.071           0.006           0.040   \n                  (0.088)         (0.161)         (0.057)   \nwp_right2           0.241          -0.379           0.070   \n                  (0.406)         (0.391)         (0.251)   \nc.neg#c.wp~2        0.220           0.194          -0.049   \n                  (0.309)         (0.402)         (0.200)   \nvid_order          -0.133***       -0.048          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.100           0.112          -0.178*  \n                  (0.132)         (0.152)         (0.082)   \nage                -0.011           0.010           0.001   \n                  (0.023)         (0.039)         (0.007)   \nincome             -0.392          -0.043           0.451*  \n                  (0.300)         (0.377)         (0.228)   \nuniversity         -0.254          -0.100           0.167   \n                  (0.188)         (0.292)         (0.124)   \n_cons               1.094           0.098          -0.090   \n                  (0.684)         (0.867)         (0.304)   \n------------------------------------------------------------\nr2_w                0.075           0.016           0.101   \nr2_b                0.154           0.163           0.205   \nr2_o                0.095           0.035           0.129   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g)\n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.063          -0.060           0.082          -0.097   \n                  (0.170)         (0.080)         (0.152)         (0.069)   \nwp_right2           0.139           0.236           0.283           0.017   \n                  (0.484)         (0.246)         (0.252)         (0.137)   \nc.neg#c.wp~2       -0.004           0.208          -0.067           0.160   \n                  (0.445)         (0.211)         (0.252)         (0.112)   \nvid_order          -0.099**        -0.087***       -0.062*         -0.020*  \n                  (0.034)         (0.021)         (0.026)         (0.009)   \nfemale              0.073          -0.090           0.110          -0.008   \n                  (0.150)         (0.102)         (0.104)         (0.048)   \nage                -0.046          -0.004           0.005           0.003   \n                  (0.049)         (0.002)         (0.005)         (0.002)   \nincome             -0.389           0.094          -0.058           0.210   \n                  (0.291)         (0.160)         (0.263)         (0.146)   \nuniversity         -0.055           0.012          -0.075           0.015   \n                  (0.233)         (0.098)         (0.159)         (0.048)   \n_cons               1.526           0.390*         -0.066          -0.091   \n                  (1.120)         (0.195)         (0.311)         (0.134)   \n----------------------------------------------------------------------------\nr2_w                0.052           0.108           0.042           0.023   \nr2_b                0.189           0.331           0.225           0.112   \nr2_o                0.075           0.144           0.073           0.044   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.101          -0.012           0.051   \n                  (0.068)         (0.082)         (0.056)   \nwp_right2           0.108           0.012           0.125   \n                  (0.184)         (0.302)         (0.157)   \nc.neg#c.wp~2        0.198           0.274           0.005   \n                  (0.173)         (0.235)         (0.132)   \nvid_order          -0.025          -0.077***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.094          -0.097          -0.033   \n                  (0.085)         (0.110)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.425          -0.094          -0.010   \n                  (0.217)         (0.220)         (0.120)   \nuniversity          0.051          -0.054           0.078   \n                  (0.087)         (0.149)         (0.062)   \n_cons               0.161           0.480*         -0.006   \n                  (0.195)         (0.225)         (0.141)   \n------------------------------------------------------------\nr2_w                0.028           0.086           0.020   \nr2_b                0.219           0.058           0.026   \nr2_o                0.068           0.078           0.022   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==1 , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==1 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==1 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==1 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==1 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==1 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==1 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g)\n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.023          -0.042           0.026          -0.134   \n                  (0.032)         (0.159)         (0.140)         (0.091)   \nwp_right2          -0.108          -1.279*         -0.197          -0.434   \n                  (0.077)         (0.604)         (0.776)         (0.296)   \nc.neg#c.wp~2       -0.078           0.080           0.384           0.335   \n                  (0.068)         (0.393)         (0.517)         (0.267)   \nvid_order          -0.078***       -0.063          -0.065          -0.021   \n                  (0.008)         (0.048)         (0.055)         (0.031)   \nfemale             -0.011          -0.378           0.647          -0.244   \n                  (0.034)         (0.224)         (0.342)         (0.148)   \nage                 0.001          -0.082***        0.030           0.000   \n                  (0.001)         (0.021)         (0.035)         (0.005)   \nincome             -0.001           1.338**        -0.133          -0.107   \n                  (0.072)         (0.514)         (0.608)         (0.302)   \nuniversity         -0.054           0.166          -0.505           0.092   \n                  (0.036)         (0.236)         (0.461)         (0.159)   \n_cons               0.327***        2.241***       -0.580           0.366   \n                  (0.083)         (0.635)         (1.076)         (0.294)   \n----------------------------------------------------------------------------\nr2_w                0.079           0.084           0.141           0.136   \nr2_b                0.022           0.401           0.206           0.222   \nr2_o                0.048           0.281           0.183           0.181   \nN                1866.000          70.000          64.000          54.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.080           0.010           0.040   \n                  (0.146)         (0.156)         (0.039)   \nwp_right2          -0.047          -0.172          -0.104   \n                  (0.518)         (0.690)         (0.248)   \nc.neg#c.wp~2       -0.405          -0.361          -0.038   \n                  (0.390)         (0.305)         (0.115)   \nvid_order          -0.111**        -0.057          -0.024   \n                  (0.041)         (0.033)         (0.018)   \nfemale              0.079           0.095          -0.050   \n                  (0.181)         (0.190)         (0.086)   \nage                 0.001           0.022           0.002   \n                  (0.008)         (0.018)         (0.003)   \nincome             -0.199           0.300           0.240   \n                  (0.523)         (0.463)         (0.183)   \nuniversity         -0.019          -0.177           0.023   \n                  (0.185)         (0.278)         (0.085)   \n_cons               0.424          -0.290          -0.093   \n                  (0.442)         (0.644)         (0.199)   \n------------------------------------------------------------\nr2_w                0.156           0.271           0.123   \nr2_b                0.105           0.078           0.078   \nr2_o                0.129           0.156           0.099   \nN                  72.000         112.000          70.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==1 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==1 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==1 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==1 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==1 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==1 , re \n.   estimates store M\n.   esttab H I J , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.153           0.026          -0.001   \n                  (0.195)         (0.103)         (0.421)   \nwp_right2          -1.049*         -0.082           0.116   \n                  (0.450)         (0.328)         (0.574)   \nc.neg#c.wp~2       -0.007          -0.027          -0.372   \n                  (0.488)         (0.158)         (0.658)   \nvid_order          -0.073          -0.057**        -0.109*  \n                  (0.038)         (0.022)         (0.048)   \nfemale             -0.368*         -0.020          -0.005   \n                  (0.148)         (0.114)         (0.210)   \nage                 0.002          -0.000           0.007   \n                  (0.008)         (0.006)         (0.014)   \nincome             -0.046          -0.153          -0.110   \n                  (0.355)         (0.224)         (0.440)   \nuniversity          0.040          -0.005           0.074   \n                  (0.147)         (0.119)         (0.245)   \n_cons               0.950*          0.359           0.125   \n                  (0.395)         (0.298)         (0.617)   \n------------------------------------------------------------\nr2_w                0.103           0.098           0.184   \nr2_b                0.268           0.031           0.012   \nr2_o                0.187           0.055           0.092   \nN                 102.000         120.000         100.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.129          -0.075          -0.149   \n                  (0.133)         (0.235)         (0.283)   \nwp_right2           0.192          -0.321          -1.040   \n                  (0.466)         (0.514)         (1.034)   \nc.neg#c.wp~2        0.391           0.441           0.808   \n                  (0.474)         (0.585)         (1.003)   \nvid_order          -0.147***       -0.053          -0.040   \n                  (0.037)         (0.051)         (0.022)   \nfemale             -0.005           0.150           0.091   \n                  (0.154)         (0.198)         (0.115)   \nage                -0.004          -0.018          -0.012   \n                  (0.027)         (0.052)         (0.010)   \nincome             -0.159          -0.785          -0.572   \n                  (0.348)         (0.491)         (0.320)   \nuniversity         -0.432*         -0.150          -0.148   \n                  (0.218)         (0.387)         (0.173)   \n_cons               1.067           0.943           1.096*  \n                  (0.795)         (1.262)         (0.508)   \n------------------------------------------------------------\nr2_w                0.313           0.019           0.135   \nr2_b                0.022           0.222           0.138   \nr2_o                0.151           0.085           0.128   \nN                 142.000          64.000          74.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==1 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==1 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==1 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==1 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==1 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==1 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==1 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g)\n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.209          -0.123           0.414          -0.036   \n                  (0.333)         (0.094)         (0.236)         (0.112)   \nwp_right2           0.684          -0.572          -0.455           0.015   \n                  (0.892)         (0.485)         (0.475)         (0.296)   \nc.neg#c.wp~2       -0.234           0.279          -0.423           0.038   \n                  (0.890)         (0.247)         (0.386)         (0.179)   \nvid_order          -0.210**        -0.011          -0.071          -0.024   \n                  (0.065)         (0.033)         (0.046)         (0.023)   \nfemale              0.149          -0.176          -0.031          -0.056   \n                  (0.240)         (0.201)         (0.195)         (0.097)   \nage                -0.094          -0.008           0.005           0.000   \n                  (0.077)         (0.005)         (0.010)         (0.005)   \nincome             -0.066           0.141          -0.139          -0.328   \n                  (0.465)         (0.319)         (0.496)         (0.297)   \nuniversity          0.554          -0.127           0.351          -0.037   \n                  (0.373)         (0.193)         (0.301)         (0.098)   \n_cons               1.898           0.894*          0.031           0.253   \n                  (1.785)         (0.403)         (0.551)         (0.277)   \n----------------------------------------------------------------------------\nr2_w                0.345           0.059           0.187           0.067   \nr2_b                0.189           0.240           0.218           0.026   \nr2_o                0.273           0.171           0.198           0.036   \nN                  72.000          64.000          64.000          96.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.119           0.040           0.021   \n                  (0.171)         (0.147)         (0.096)   \nwp_right2           0.102          -0.522           0.280   \n                  (0.335)         (0.493)         (0.223)   \nc.neg#c.wp~2       -0.154          -0.206           0.064   \n                  (0.434)         (0.418)         (0.228)   \nvid_order          -0.100**        -0.089*         -0.089***\n                  (0.033)         (0.043)         (0.020)   \nfemale              0.037           0.025           0.048   \n                  (0.154)         (0.180)         (0.086)   \nage                -0.003           0.002           0.001   \n                  (0.006)         (0.007)         (0.004)   \nincome              0.644          -0.050          -0.095   \n                  (0.397)         (0.363)         (0.169)   \nuniversity         -0.118          -0.185          -0.016   \n                  (0.158)         (0.245)         (0.086)   \n_cons               0.115           0.472           0.199   \n                  (0.351)         (0.412)         (0.199)   \n------------------------------------------------------------\nr2_w                0.149           0.055           0.073   \nr2_b                0.339           0.197           0.052   \nr2_o                0.217           0.069           0.061   \nN                  62.000          96.000         368.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.  \n. * Table A4 Row 2 \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(56,936 real changes made, 39,228 to missing)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (p_negative==1 | p_negative==0) , re \n.   estimates store A  \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (threatening==1 | p_negative==0) , re \n.   estimates store B  \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (disgusting==1 | p_negative==0) , re \n.   estimates store C\n.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.014***        0.010** \n                  (0.003)         (0.004)         (0.004)   \nwp_right2           0.050           0.056           0.042   \n                  (0.037)         (0.038)         (0.038)   \nc.neg#c.wp~2       -0.012          -0.014          -0.008   \n                  (0.007)         (0.009)         (0.008)   \npho_order           0.002***        0.003***        0.002***\n                  (0.000)         (0.001)         (0.001)   \nfemale              0.012           0.005           0.008   \n                  (0.007)         (0.008)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.018          -0.007          -0.020   \n                  (0.015)         (0.017)         (0.017)   \nuniversity          0.006           0.008           0.004   \n                  (0.007)         (0.008)         (0.008)   \n_cons              -0.070**        -0.090***       -0.071** \n                  (0.023)         (0.024)         (0.025)   \n------------------------------------------------------------\nr2_w                0.003           0.004           0.003   \nr2_b                0.015           0.014           0.007   \nr2_o                0.003           0.004           0.003   \nN               15263.000       12049.000       11245.000   \nN_g               804.000         804.000         804.000   \n------------------------------------------------------------\n.    \n.    \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (p_negative==1 | p_negative==0) , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (p_negative==1 | p_\n> negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.007   \n                  (0.003)         (0.017)         (0.013)   \nwp_right2           0.050          -0.105           0.009   \n                  (0.037)         (0.214)         (0.220)   \nc.neg#c.wp~2       -0.012           0.011           0.015   \n                  (0.007)         (0.042)         (0.040)   \npho_order           0.002***        0.005*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.023           0.070   \n                  (0.007)         (0.037)         (0.061)   \nage                -0.000          -0.002           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.018          -0.087          -0.145   \n                  (0.015)         (0.079)         (0.118)   \nuniversity          0.006           0.015           0.121   \n                  (0.007)         (0.037)         (0.063)   \n_cons              -0.070**         0.008          -0.178   \n                  (0.023)         (0.131)         (0.142)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.014   \nr2_b                0.015           0.178           0.232   \nr2_o                0.003           0.018           0.032   \nN               15263.000         623.000         513.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003          -0.009           0.007   \n                  (0.016)         (0.027)         (0.009)   \nwp_right2          -0.288          -0.071          -0.026   \n                  (0.230)         (0.274)         (0.145)   \nc.neg#c.wp~2        0.037           0.030          -0.004   \n                  (0.044)         (0.052)         (0.026)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.031           0.039          -0.067*  \n                  (0.040)         (0.036)         (0.028)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome             -0.005           0.013           0.036   \n                  (0.115)         (0.095)         (0.060)   \nuniversity         -0.051           0.012          -0.013   \n                  (0.041)         (0.053)         (0.028)   \n_cons               0.073          -0.070          -0.060   \n                  (0.125)         (0.174)         (0.075)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.012   \nr2_b                0.155           0.056           0.192   \nr2_o                0.008           0.004           0.027   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (p_negative==1 | p_\n> negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (p_negative==1 | p_\n> negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.030*          0.014           0.005           0.012   \n                  (0.015)         (0.015)         (0.017)         (0.013)   \nwp_right2           0.212           0.020           0.061           0.322   \n                  (0.197)         (0.124)         (0.136)         (0.205)   \nc.neg#c.wp~2       -0.029          -0.015          -0.015          -0.041   \n                  (0.038)         (0.023)         (0.026)         (0.037)   \npho_order           0.005*          0.003*          0.001           0.001   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.018           0.020           0.026           0.004   \n                  (0.030)         (0.022)         (0.025)         (0.039)   \nage                 0.000          -0.000          -0.001           0.002   \n                  (0.002)         (0.001)         (0.002)         (0.005)   \nincome             -0.046          -0.025          -0.029          -0.029   \n                  (0.074)         (0.043)         (0.055)         (0.078)   \nuniversity          0.072*         -0.022           0.020           0.007   \n                  (0.030)         (0.023)         (0.029)         (0.055)   \n_cons              -0.283**        -0.045          -0.014          -0.143   \n                  (0.106)         (0.090)         (0.104)         (0.173)   \n----------------------------------------------------------------------------\nr2_w                0.016           0.006           0.002           0.003   \nr2_b                0.267           0.073           0.064           0.115   \nr2_o                0.024           0.011           0.004           0.008   \nN                 969.000        1140.000         911.000         456.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.037           0.008           0.027   \n                  (0.019)         (0.010)         (0.026)   \nwp_right2          -0.385           0.020           0.061   \n                  (0.247)         (0.178)         (0.359)   \nc.neg#c.wp~2        0.072          -0.012          -0.015   \n                  (0.048)         (0.035)         (0.068)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.032          -0.032           0.019   \n                  (0.044)         (0.026)         (0.054)   \nage                 0.005          -0.002           0.014   \n                  (0.011)         (0.002)         (0.018)   \nincome             -0.145           0.120           0.058   \n                  (0.106)         (0.072)         (0.105)   \nuniversity          0.133          -0.004          -0.105   \n                  (0.119)         (0.039)         (0.085)   \n_cons              -0.064          -0.048          -0.282   \n                  (0.266)         (0.107)         (0.423)   \n------------------------------------------------------------\nr2_w                0.017           0.011           0.007   \nr2_b                0.212           0.124           0.095   \nr2_o                0.030           0.017           0.010   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (p_negative==1 | p_ne\n> gative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.046***        0.057**        -0.009   \n                  (0.013)         (0.019)         (0.011)   \nwp_right2           0.201           0.402*         -0.093   \n                  (0.191)         (0.164)         (0.088)   \nc.neg#c.wp~2       -0.077*         -0.072*          0.019   \n                  (0.035)         (0.032)         (0.017)   \npho_order           0.001          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.003          -0.014           0.016   \n                  (0.043)         (0.032)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.001          -0.061          -0.037   \n                  (0.068)         (0.080)         (0.043)   \nuniversity         -0.013          -0.036           0.001   \n                  (0.041)         (0.048)         (0.014)   \n_cons              -0.133          -0.170           0.056   \n                  (0.102)         (0.127)         (0.064)   \n------------------------------------------------------------\nr2_w                0.025           0.018           0.004   \nr2_b                0.163           0.136           0.108   \nr2_o                0.033           0.022           0.006   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009           0.009           0.016   \n                  (0.011)         (0.012)         (0.011)   \nwp_right2          -0.104           0.046           0.100   \n                  (0.152)         (0.178)         (0.142)   \nc.neg#c.wp~2        0.015          -0.018          -0.019   \n                  (0.029)         (0.034)         (0.028)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.059           0.053           0.005   \n                  (0.032)         (0.030)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.012          -0.078           0.045   \n                  (0.082)         (0.061)         (0.045)   \nuniversity          0.022          -0.053           0.021   \n                  (0.033)         (0.041)         (0.023)   \n_cons              -0.154           0.010          -0.090   \n                  (0.090)         (0.087)         (0.072)   \n------------------------------------------------------------\nr2_w                0.009           0.002           0.002   \nr2_b                0.193           0.152           0.033   \nr2_o                0.020           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.              \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (threatening==1 | p_negative==0) , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (threatening==1 | p\n> _negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***       -0.024           0.011   \n                  (0.004)         (0.021)         (0.016)   \nwp_right2           0.056          -0.334           0.037   \n                  (0.038)         (0.232)         (0.242)   \nc.neg#c.wp~2       -0.014           0.097           0.014   \n                  (0.009)         (0.051)         (0.048)   \npho_order           0.003***        0.007**         0.007*  \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.005          -0.004           0.102   \n                  (0.008)         (0.042)         (0.074)   \nage                -0.000           0.001           0.000   \n                  (0.000)         (0.004)         (0.003)   \nincome             -0.007          -0.119          -0.208   \n                  (0.017)         (0.092)         (0.144)   \nuniversity          0.008           0.037           0.153*  \n                  (0.008)         (0.043)         (0.077)   \n_cons              -0.090***       -0.036          -0.224   \n                  (0.024)         (0.148)         (0.169)   \n------------------------------------------------------------\nr2_w                0.004           0.028           0.022   \nr2_b                0.014           0.135           0.250   \nr2_o                0.004           0.031           0.051   \nN               12049.000         492.000         405.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.006           0.006   \n                  (0.019)         (0.030)         (0.009)   \nwp_right2          -0.277           0.065           0.013   \n                  (0.240)         (0.269)         (0.140)   \nc.neg#c.wp~2        0.033          -0.002          -0.005   \n                  (0.052)         (0.058)         (0.027)   \npho_order           0.003           0.002           0.002   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.023           0.018          -0.047   \n                  (0.045)         (0.038)         (0.031)   \nage                -0.001          -0.000           0.000   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.003           0.066           0.008   \n                  (0.129)         (0.099)         (0.066)   \nuniversity         -0.048          -0.031           0.001   \n                  (0.046)         (0.055)         (0.031)   \n_cons               0.065          -0.085          -0.070   \n                  (0.136)         (0.175)         (0.077)   \n------------------------------------------------------------\nr2_w                0.004           0.001           0.005   \nr2_b                0.136           0.025           0.106   \nr2_o                0.009           0.002           0.017   \nN                 540.000         825.000         525.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (threatening==1 | p\n> _negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (threatening==1 | p\n> _negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.023           0.019           0.006           0.002   \n                  (0.018)         (0.019)         (0.021)         (0.016)   \nwp_right2           0.154           0.052           0.087           0.254   \n                  (0.206)         (0.139)         (0.148)         (0.237)   \nc.neg#c.wp~2       -0.008          -0.027          -0.020          -0.024   \n                  (0.045)         (0.029)         (0.032)         (0.046)   \npho_order           0.007**         0.004**         0.002           0.000   \n                  (0.002)         (0.001)         (0.002)         (0.003)   \nfemale              0.032           0.018           0.003           0.021   \n                  (0.034)         (0.028)         (0.029)         (0.052)   \nage                 0.000          -0.000          -0.001           0.003   \n                  (0.002)         (0.001)         (0.002)         (0.007)   \nincome             -0.095          -0.007           0.010          -0.082   \n                  (0.082)         (0.054)         (0.063)         (0.105)   \nuniversity          0.069*         -0.023           0.017          -0.005   \n                  (0.034)         (0.029)         (0.034)         (0.074)   \n_cons              -0.260*         -0.077          -0.051          -0.095   \n                  (0.114)         (0.103)         (0.116)         (0.225)   \n----------------------------------------------------------------------------\nr2_w                0.020           0.010           0.004           0.002   \nr2_b                0.362           0.063           0.007           0.166   \nr2_o                0.032           0.015           0.005           0.015   \nN                 765.000         900.000         720.000         360.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.050*          0.005           0.012   \n                  (0.024)         (0.012)         (0.028)   \nwp_right2          -0.389          -0.005          -0.051   \n                  (0.265)         (0.189)         (0.340)   \nc.neg#c.wp~2        0.078          -0.001           0.007   \n                  (0.059)         (0.042)         (0.073)   \npho_order           0.008**         0.004*         -0.002   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.076          -0.045          -0.016   \n                  (0.050)         (0.029)         (0.055)   \nage                 0.005          -0.003           0.007   \n                  (0.013)         (0.002)         (0.018)   \nincome             -0.079           0.066           0.006   \n                  (0.121)         (0.081)         (0.106)   \nuniversity          0.140          -0.013           0.016   \n                  (0.136)         (0.044)         (0.085)   \n_cons              -0.063           0.014          -0.156   \n                  (0.299)         (0.118)         (0.424)   \n------------------------------------------------------------\nr2_w                0.026           0.013           0.004   \nr2_b                0.229           0.082           0.032   \nr2_o                0.042           0.017           0.004   \nN                 465.000         555.000         540.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (threatening==1 | p_n\n> egative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.062***        0.080***        0.000   \n                  (0.016)         (0.022)         (0.013)   \nwp_right2           0.262           0.497**        -0.057   \n                  (0.200)         (0.167)         (0.094)   \nc.neg#c.wp~2       -0.101*         -0.112**         0.004   \n                  (0.042)         (0.037)         (0.021)   \npho_order           0.002           0.002           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.006          -0.034           0.031   \n                  (0.045)         (0.034)         (0.016)   \nage                -0.000          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.016           0.056          -0.050   \n                  (0.071)         (0.087)         (0.050)   \nuniversity          0.003          -0.050          -0.001   \n                  (0.043)         (0.053)         (0.016)   \n_cons              -0.210          -0.279*          0.025   \n                  (0.107)         (0.134)         (0.070)   \n------------------------------------------------------------\nr2_w                0.040           0.029           0.003   \nr2_b                0.127           0.221           0.229   \nr2_o                0.046           0.036           0.011   \nN                 480.000         480.000         720.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.024           0.003           0.018   \n                  (0.014)         (0.014)         (0.013)   \nwp_right2          -0.062          -0.024           0.092   \n                  (0.164)         (0.187)         (0.149)   \nc.neg#c.wp~2       -0.020           0.016          -0.012   \n                  (0.035)         (0.040)         (0.033)   \npho_order           0.001           0.002           0.001   \n                  (0.002)         (0.002)         (0.002)   \nfemale              0.042           0.029          -0.005   \n                  (0.040)         (0.036)         (0.024)   \nage                 0.003          -0.001          -0.002*  \n                  (0.002)         (0.001)         (0.001)   \nincome              0.106          -0.114           0.070   \n                  (0.103)         (0.071)         (0.050)   \nuniversity         -0.016          -0.042           0.035   \n                  (0.041)         (0.048)         (0.025)   \n_cons              -0.284**         0.064          -0.109   \n                  (0.104)         (0.095)         (0.077)   \n------------------------------------------------------------\nr2_w                0.013           0.003           0.003   \nr2_b                0.248           0.111           0.079   \nr2_o                0.033           0.011           0.007   \nN                 462.000         715.000        2085.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.              \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (disgusting==1 | p_negative==0) , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (disgusting==1 | p_\n> negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010**         0.022           0.003   \n                  (0.004)         (0.019)         (0.015)   \nwp_right2           0.042          -0.018           0.044   \n                  (0.038)         (0.213)         (0.207)   \nc.neg#c.wp~2       -0.008          -0.040           0.007   \n                  (0.008)         (0.047)         (0.045)   \npho_order           0.002***        0.008**         0.006*  \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.008          -0.020           0.073   \n                  (0.008)         (0.041)         (0.053)   \nage                -0.000          -0.005           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.020          -0.027          -0.052   \n                  (0.017)         (0.088)         (0.104)   \nuniversity          0.004          -0.012           0.114*  \n                  (0.008)         (0.041)         (0.055)   \n_cons              -0.071**        -0.008          -0.221   \n                  (0.025)         (0.141)         (0.132)   \n------------------------------------------------------------\nr2_w                0.003           0.021           0.011   \nr2_b                0.007           0.230           0.245   \nr2_o                0.003           0.035           0.029   \nN               11245.000         459.000         378.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.001          -0.022           0.007   \n                  (0.018)         (0.031)         (0.011)   \nwp_right2          -0.327          -0.133          -0.026   \n                  (0.235)         (0.282)         (0.159)   \nc.neg#c.wp~2        0.037           0.050          -0.003   \n                  (0.050)         (0.060)         (0.031)   \npho_order           0.003           0.002           0.006***\n                  (0.003)         (0.003)         (0.002)   \nfemale              0.049           0.020          -0.061   \n                  (0.047)         (0.043)         (0.035)   \nage                -0.001          -0.000          -0.000   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.021          -0.038           0.066   \n                  (0.136)         (0.112)         (0.076)   \nuniversity         -0.068           0.059          -0.008   \n                  (0.048)         (0.062)         (0.035)   \n_cons               0.046          -0.019          -0.119   \n                  (0.139)         (0.188)         (0.089)   \n------------------------------------------------------------\nr2_w                0.007           0.002           0.027   \nr2_b                0.135           0.046           0.150   \nr2_o                0.016           0.005           0.042   \nN                 504.000         770.000         490.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (disgusting==1 | p_\n> negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (disgusting==1 | p_\n> negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.030           0.010          -0.006           0.014   \n                  (0.017)         (0.018)         (0.020)         (0.016)   \nwp_right2           0.224           0.003           0.022           0.397   \n                  (0.196)         (0.125)         (0.140)         (0.233)   \nc.neg#c.wp~2       -0.041          -0.007           0.003          -0.038   \n                  (0.042)         (0.027)         (0.030)         (0.044)   \npho_order           0.005*          0.002           0.001           0.003   \n                  (0.002)         (0.001)         (0.002)         (0.003)   \nfemale             -0.015           0.022           0.041           0.014   \n                  (0.034)         (0.023)         (0.029)         (0.055)   \nage                 0.002          -0.001          -0.002           0.006   \n                  (0.002)         (0.001)         (0.002)         (0.007)   \nincome             -0.034          -0.030          -0.054           0.087   \n                  (0.082)         (0.045)         (0.063)         (0.110)   \nuniversity          0.058          -0.008           0.013          -0.017   \n                  (0.034)         (0.024)         (0.033)         (0.077)   \n_cons              -0.298**        -0.015           0.041          -0.334   \n                  (0.111)         (0.092)         (0.111)         (0.234)   \n----------------------------------------------------------------------------\nr2_w                0.014           0.004           0.001           0.008   \nr2_b                0.172           0.046           0.130           0.123   \nr2_o                0.022           0.008           0.007           0.018   \nN                 714.000         840.000         671.000         336.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.031           0.008           0.043   \n                  (0.024)         (0.011)         (0.032)   \nwp_right2          -0.394           0.031           0.072   \n                  (0.265)         (0.168)         (0.390)   \nc.neg#c.wp~2        0.087          -0.021          -0.044   \n                  (0.059)         (0.037)         (0.084)   \npho_order           0.009**         0.005**        -0.005   \n                  (0.003)         (0.002)         (0.004)   \nfemale             -0.058          -0.040          -0.026   \n                  (0.053)         (0.027)         (0.066)   \nage                 0.023          -0.003          -0.005   \n                  (0.013)         (0.002)         (0.021)   \nincome             -0.111           0.110           0.187   \n                  (0.126)         (0.076)         (0.128)   \nuniversity          0.099           0.015          -0.185   \n                  (0.142)         (0.041)         (0.103)   \n_cons              -0.424          -0.048           0.162   \n                  (0.313)         (0.108)         (0.510)   \n------------------------------------------------------------\nr2_w                0.019           0.020           0.013   \nr2_b                0.289           0.133           0.183   \nr2_o                0.041           0.027           0.025   \nN                 434.000         518.000         504.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (disgusting==1 | p_ne\n> gative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.021           0.036          -0.019   \n                  (0.014)         (0.021)         (0.012)   \nwp_right2           0.078           0.310          -0.120   \n                  (0.183)         (0.160)         (0.088)   \nc.neg#c.wp~2       -0.031          -0.042           0.033   \n                  (0.038)         (0.035)         (0.019)   \npho_order           0.002          -0.002           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.015          -0.029           0.005   \n                  (0.045)         (0.035)         (0.016)   \nage                 0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.052          -0.141          -0.035   \n                  (0.071)         (0.090)         (0.049)   \nuniversity         -0.004          -0.060          -0.002   \n                  (0.043)         (0.054)         (0.016)   \n_cons              -0.121          -0.036           0.089   \n                  (0.103)         (0.131)         (0.066)   \n------------------------------------------------------------\nr2_w                0.008           0.010           0.005   \nr2_b                0.058           0.216           0.030   \nr2_o                0.012           0.026           0.006   \nN                 448.000         448.000         672.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.010           0.013           0.016   \n                  (0.012)         (0.015)         (0.013)   \nwp_right2          -0.190           0.095           0.084   \n                  (0.147)         (0.199)         (0.147)   \nc.neg#c.wp~2        0.049          -0.038          -0.018   \n                  (0.031)         (0.044)         (0.032)   \npho_order          -0.000           0.003           0.001   \n                  (0.002)         (0.002)         (0.002)   \nfemale              0.026           0.067           0.013   \n                  (0.038)         (0.037)         (0.025)   \nage                 0.002          -0.001           0.000   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.048          -0.079           0.066   \n                  (0.096)         (0.075)         (0.052)   \nuniversity          0.033          -0.056           0.015   \n                  (0.038)         (0.051)         (0.026)   \n_cons              -0.108          -0.021          -0.150   \n                  (0.096)         (0.102)         (0.078)   \n------------------------------------------------------------\nr2_w                0.008           0.003           0.002   \nr2_b                0.166           0.157           0.015   \nr2_o                0.021           0.013           0.003   \nN                 432.000         667.000        1946.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                                                  \n.                                  \n. * Table A5\n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negative\n(56,936 real changes made, 17,708 to missing)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 & (stimulus==\"v_11\" | v_negative==0\n> ) , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 11\" | v_negative==0) , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 11\" | v_negative==0) , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.116           0.047          -0.117          -0.093   \n                  (0.065)         (0.330)         (0.350)         (0.186)   \nwp_right2           0.019          -0.432          -0.458          -0.335   \n                  (0.070)         (0.437)         (0.780)         (0.310)   \nc.neg#c.wp~2       -0.072           0.385           1.296           0.158   \n                  (0.146)         (0.858)         (1.162)         (0.544)   \nvid_order          -0.076***       -0.035          -0.100*         -0.045   \n                  (0.007)         (0.036)         (0.041)         (0.024)   \nfemale             -0.022          -0.013           0.201           0.084   \n                  (0.029)         (0.148)         (0.326)         (0.145)   \nage                 0.002           0.006           0.041          -0.005   \n                  (0.001)         (0.015)         (0.033)         (0.005)   \nincome             -0.035           0.060          -0.073          -0.049   \n                  (0.060)         (0.334)         (0.578)         (0.284)   \nuniversity          0.008          -0.016          -0.139          -0.087   \n                  (0.030)         (0.155)         (0.447)         (0.147)   \n_cons               0.177*          0.104          -0.714           0.530   \n                  (0.070)         (0.459)         (1.039)         (0.324)   \n----------------------------------------------------------------------------\nr2_w                0.054           0.049           0.121           0.058   \nr2_b                0.035           0.026           0.147           0.100   \nr2_o                0.048           0.039           0.140           0.078   \nN                2872.000         114.000          95.000          83.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.453           0.043          -0.227   \n                  (0.316)         (0.594)         (0.248)   \nwp_right2           0.695          -0.186          -0.074   \n                  (0.513)         (0.569)         (0.357)   \nc.neg#c.wp~2       -0.454          -0.060           1.006   \n                  (0.820)         (1.130)         (0.738)   \nvid_order          -0.064          -0.121***       -0.051*  \n                  (0.036)         (0.031)         (0.025)   \nfemale              0.008          -0.098           0.036   \n                  (0.161)         (0.145)         (0.113)   \nage                 0.007          -0.013           0.002   \n                  (0.007)         (0.015)         (0.004)   \nincome              0.144           0.468           0.279   \n                  (0.473)         (0.351)         (0.256)   \nuniversity          0.317          -0.193           0.052   \n                  (0.167)         (0.217)         (0.110)   \n_cons              -0.728           0.879          -0.110   \n                  (0.442)         (0.520)         (0.270)   \n------------------------------------------------------------\nr2_w                0.090           0.086           0.033   \nr2_b                0.153           0.155           0.270   \nr2_o                0.130           0.112           0.076   \nN                 113.000         172.000         107.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 11\" | v_negative==0) , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 11\" | v_negative==0) , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.042           0.212           0.366   \n                  (0.395)         (0.384)         (0.319)   \nwp_right2          -0.269           0.080          -0.286   \n                  (0.489)         (0.201)         (0.269)   \nc.neg#c.wp~2        0.781          -0.235          -0.964   \n                  (0.974)         (0.585)         (0.497)   \nvid_order          -0.141***       -0.058***       -0.086***\n                  (0.037)         (0.014)         (0.023)   \nfemale             -0.138          -0.132*         -0.070   \n                  (0.150)         (0.060)         (0.098)   \nage                -0.005           0.001           0.002   \n                  (0.008)         (0.003)         (0.007)   \nincome             -0.342           0.145           0.072   \n                  (0.369)         (0.124)         (0.202)   \nuniversity          0.007          -0.006          -0.219   \n                  (0.149)         (0.063)         (0.117)   \n_cons               1.050*          0.088           0.434   \n                  (0.414)         (0.172)         (0.269)   \n------------------------------------------------------------\nr2_w                0.143           0.077           0.125   \nr2_b                0.025           0.194           0.253   \nr2_o                0.110           0.117           0.149   \nN                 158.000         186.000         152.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.188           0.624           0.058   \n                  (0.254)         (0.504)         (0.187)   \nwp_right2          -0.221          -0.539           0.161   \n                  (0.484)         (0.512)         (0.305)   \nc.neg#c.wp~2        0.156          -0.935           0.184   \n                  (0.893)         (1.299)         (0.650)   \nvid_order          -0.144***       -0.047          -0.072***\n                  (0.033)         (0.042)         (0.020)   \nfemale             -0.068           0.093          -0.142   \n                  (0.144)         (0.190)         (0.090)   \nage                -0.036           0.002           0.000   \n                  (0.025)         (0.051)         (0.009)   \nincome             -0.259          -0.196           0.338   \n                  (0.327)         (0.477)         (0.253)   \nuniversity         -0.244          -0.110           0.257   \n                  (0.203)         (0.352)         (0.143)   \n_cons               1.754*          0.322          -0.093   \n                  (0.736)         (1.123)         (0.359)   \n------------------------------------------------------------\nr2_w                0.078           0.036           0.127   \nr2_b                0.177           0.219           0.170   \nr2_o                0.115           0.067           0.152   \nN                 222.000         102.000         115.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_11\n> \" | v_negative==0) , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.276           0.224           1.139**        -0.392   \n                  (0.641)         (0.226)         (0.401)         (0.224)   \nwp_right2           0.376           0.241           0.234           0.003   \n                  (0.699)         (0.328)         (0.337)         (0.197)   \nc.neg#c.wp~2        0.019          -0.616          -1.701**         0.607   \n                  (1.601)         (0.684)         (0.657)         (0.371)   \nvid_order          -0.107*         -0.074**        -0.082**        -0.033*  \n                  (0.048)         (0.028)         (0.031)         (0.014)   \nfemale              0.266           0.077           0.032           0.025   \n                  (0.204)         (0.131)         (0.122)         (0.065)   \nage                -0.023          -0.001           0.009           0.002   \n                  (0.068)         (0.003)         (0.006)         (0.003)   \nincome             -0.603           0.237          -0.248          -0.053   \n                  (0.385)         (0.214)         (0.310)         (0.202)   \nuniversity          0.057          -0.041          -0.034           0.047   \n                  (0.310)         (0.128)         (0.179)         (0.063)   \n_cons               0.853           0.034          -0.022           0.082   \n                  (1.553)         (0.259)         (0.377)         (0.187)   \n----------------------------------------------------------------------------\nr2_w                0.086           0.100           0.212           0.067   \nr2_b                0.205           0.067           0.072           0.074   \nr2_o                0.119           0.090           0.180           0.072   \nN                 111.000          97.000          97.000         146.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.205          -0.192           0.001   \n                  (0.229)         (0.264)         (0.155)   \nwp_right2          -0.059          -0.217           0.073   \n                  (0.264)         (0.324)         (0.236)   \nc.neg#c.wp~2        0.605           0.842           0.175   \n                  (0.539)         (0.710)         (0.378)   \nvid_order          -0.035          -0.112***       -0.040** \n                  (0.025)         (0.027)         (0.014)   \nfemale              0.187          -0.121          -0.043   \n                  (0.114)         (0.110)         (0.089)   \nage                 0.005          -0.002           0.004   \n                  (0.004)         (0.004)         (0.004)   \nincome             -0.620*          0.098          -0.062   \n                  (0.288)         (0.223)         (0.173)   \nuniversity          0.019          -0.180           0.162   \n                  (0.115)         (0.147)         (0.089)   \n_cons               0.243           0.656**        -0.103   \n                  (0.264)         (0.249)         (0.200)   \n------------------------------------------------------------\nr2_w                0.046           0.131           0.018   \nr2_b                0.302           0.203           0.046   \nr2_o                0.146           0.156           0.032   \nN                  97.000         140.000         565.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negative\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 & (stimulus==\"v_12\" | v_negative==0\n> ) , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 12\" | v_negative==0) , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 12\" | v_negative==0) , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.005          -0.470          -0.029          -0.283   \n                  (0.063)         (0.393)         (0.259)         (0.158)   \nwp_right2           0.020          -0.409          -0.407          -0.386   \n                  (0.070)         (0.453)         (0.755)         (0.277)   \nc.neg#c.wp~2        0.264           1.973*          0.586           0.284   \n                  (0.141)         (1.002)         (0.844)         (0.480)   \nvid_order          -0.078***       -0.032          -0.130**        -0.037   \n                  (0.007)         (0.037)         (0.041)         (0.023)   \nfemale             -0.028          -0.007           0.223           0.072   \n                  (0.029)         (0.159)         (0.308)         (0.132)   \nage                 0.001           0.021           0.041          -0.004   \n                  (0.001)         (0.015)         (0.031)         (0.005)   \nincome              0.005          -0.298          -0.117           0.078   \n                  (0.060)         (0.378)         (0.545)         (0.257)   \nuniversity         -0.007           0.114          -0.210          -0.119   \n                  (0.030)         (0.166)         (0.418)         (0.141)   \n_cons               0.210**        -0.168          -0.529           0.466   \n                  (0.070)         (0.455)         (0.965)         (0.304)   \n----------------------------------------------------------------------------\nr2_w                0.057           0.068           0.161           0.156   \nr2_b                0.039           0.123           0.110           0.092   \nr2_o                0.050           0.088           0.154           0.118   \nN                2893.000         105.000         103.000          80.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.279           0.070          -0.439   \n                  (0.363)         (0.523)         (0.265)   \nwp_right2           0.697          -0.226          -0.218   \n                  (0.579)         (0.533)         (0.387)   \nc.neg#c.wp~2        1.160          -0.120           1.686*  \n                  (1.068)         (1.033)         (0.818)   \nvid_order          -0.137***       -0.099***       -0.040   \n                  (0.040)         (0.030)         (0.027)   \nfemale              0.119          -0.100          -0.040   \n                  (0.188)         (0.135)         (0.123)   \nage                -0.000          -0.008           0.001   \n                  (0.008)         (0.014)         (0.004)   \nincome              0.578           0.306           0.422   \n                  (0.537)         (0.329)         (0.274)   \nuniversity          0.305          -0.046          -0.034   \n                  (0.191)         (0.202)         (0.124)   \n_cons              -0.354           0.630          -0.077   \n                  (0.489)         (0.490)         (0.293)   \n------------------------------------------------------------\nr2_w                0.201           0.050           0.038   \nr2_b                0.146           0.191           0.273   \nr2_o                0.153           0.081           0.088   \nN                 112.000         173.000         107.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 12\" | v_negative==0) , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 12\" | v_negative==0) , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.188           0.440           0.160   \n                  (0.368)         (0.254)         (0.294)   \nwp_right2          -0.184           0.125          -0.211   \n                  (0.468)         (0.214)         (0.302)   \nc.neg#c.wp~2        0.848          -0.391          -0.282   \n                  (0.932)         (0.396)         (0.468)   \nvid_order          -0.162***       -0.079***       -0.099***\n                  (0.034)         (0.016)         (0.021)   \nfemale             -0.170          -0.165*         -0.024   \n                  (0.144)         (0.065)         (0.114)   \nage                -0.006           0.001          -0.003   \n                  (0.007)         (0.003)         (0.008)   \nincome             -0.207           0.105           0.289   \n                  (0.362)         (0.126)         (0.234)   \nuniversity          0.059          -0.056          -0.204   \n                  (0.143)         (0.068)         (0.133)   \n_cons               1.033**         0.192           0.465   \n                  (0.400)         (0.186)         (0.307)   \n------------------------------------------------------------\nr2_w                0.161           0.170           0.158   \nr2_b                0.146           0.220           0.129   \nr2_o                0.155           0.184           0.135   \nN                 157.000         185.000         161.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.434          -0.811           0.184   \n                  (0.276)         (0.587)         (0.197)   \nwp_right2          -0.139          -0.466           0.187   \n                  (0.498)         (0.530)         (0.329)   \nc.neg#c.wp~2        1.815           1.823          -0.690   \n                  (0.986)         (1.578)         (0.698)   \nvid_order          -0.159***       -0.088          -0.067** \n                  (0.035)         (0.048)         (0.021)   \nfemale             -0.050           0.180          -0.144   \n                  (0.148)         (0.206)         (0.100)   \nage                -0.021           0.007           0.002   \n                  (0.025)         (0.054)         (0.009)   \nincome             -0.325           0.133           0.267   \n                  (0.335)         (0.516)         (0.269)   \nuniversity         -0.247          -0.125           0.275   \n                  (0.216)         (0.396)         (0.155)   \n_cons               1.469*          0.173          -0.141   \n                  (0.745)         (1.202)         (0.378)   \n------------------------------------------------------------\nr2_w                0.062           0.075           0.113   \nr2_b                0.311           0.090           0.126   \nr2_o                0.125           0.077           0.138   \nN                 221.000          95.000         113.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_12\n> \" | v_negative==0) , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.014           0.113          -0.137          -0.127   \n                  (0.563)         (0.217)         (0.383)         (0.244)   \nwp_right2          -0.113           0.119           0.270          -0.047   \n                  (0.679)         (0.328)         (0.360)         (0.174)   \nc.neg#c.wp~2        0.373           0.381           0.339           0.260   \n                  (1.470)         (0.594)         (0.642)         (0.376)   \nvid_order          -0.061          -0.088***       -0.040          -0.028*  \n                  (0.046)         (0.025)         (0.033)         (0.013)   \nfemale             -0.062          -0.019           0.199          -0.009   \n                  (0.205)         (0.130)         (0.135)         (0.055)   \nage                -0.100          -0.004           0.008           0.004   \n                  (0.065)         (0.003)         (0.007)         (0.003)   \nincome             -0.654           0.015          -0.099           0.062   \n                  (0.381)         (0.203)         (0.340)         (0.168)   \nuniversity          0.245           0.099          -0.084          -0.000   \n                  (0.315)         (0.125)         (0.212)         (0.055)   \n_cons               2.506           0.349          -0.314          -0.000   \n                  (1.491)         (0.241)         (0.415)         (0.167)   \n----------------------------------------------------------------------------\nr2_w                0.024           0.127           0.010           0.036   \nr2_b                0.208           0.307           0.274           0.137   \nr2_o                0.080           0.167           0.105           0.068   \nN                 109.000         105.000          94.000         143.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.149           0.129           0.211   \n                  (0.216)         (0.194)         (0.157)   \nwp_right2           0.032          -0.274           0.127   \n                  (0.262)         (0.383)         (0.213)   \nc.neg#c.wp~2        0.244           0.082           0.061   \n                  (0.539)         (0.569)         (0.363)   \nvid_order          -0.016          -0.100***       -0.042** \n                  (0.025)         (0.024)         (0.015)   \nfemale              0.166          -0.201          -0.040   \n                  (0.108)         (0.132)         (0.078)   \nage                 0.001          -0.003           0.002   \n                  (0.004)         (0.005)         (0.003)   \nincome             -0.568*          0.228          -0.081   \n                  (0.285)         (0.266)         (0.152)   \nuniversity          0.033          -0.122           0.137   \n                  (0.108)         (0.180)         (0.078)   \n_cons               0.275           0.648*         -0.042   \n                  (0.258)         (0.284)         (0.180)   \n------------------------------------------------------------\nr2_w                0.020           0.106           0.046   \nr2_b                0.316           0.279           0.023   \nr2_o                0.094           0.160           0.037   \nN                 102.000         147.000         581.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.    \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negative\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 & (stimulus==\"v_13\" | v_negative==0\n> ) , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 13\" | v_negative==0) , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 13\" | v_negative==0) , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.132*         -0.325          -0.338          -0.270   \n                  (0.063)         (0.393)         (0.286)         (0.169)   \nwp_right2           0.012          -0.443          -0.656          -0.331   \n                  (0.068)         (0.450)         (0.651)         (0.253)   \nc.neg#c.wp~2        0.169          -0.045           1.548           0.619   \n                  (0.140)         (0.941)         (0.954)         (0.500)   \nvid_order          -0.083***       -0.027          -0.131**        -0.043   \n                  (0.006)         (0.037)         (0.045)         (0.024)   \nfemale             -0.043          -0.100           0.153           0.117   \n                  (0.028)         (0.155)         (0.247)         (0.118)   \nage                 0.002*         -0.003           0.037          -0.004   \n                  (0.001)         (0.015)         (0.025)         (0.004)   \nincome             -0.001          -0.081          -0.230          -0.110   \n                  (0.058)         (0.336)         (0.430)         (0.227)   \nuniversity         -0.013           0.074          -0.289          -0.045   \n                  (0.029)         (0.167)         (0.336)         (0.118)   \n_cons               0.210**         0.380          -0.226           0.479   \n                  (0.068)         (0.471)         (0.805)         (0.275)   \n----------------------------------------------------------------------------\nr2_w                0.061           0.050           0.158           0.061   \nr2_b                0.051           0.089           0.191           0.124   \nr2_o                0.057           0.061           0.170           0.080   \nN                2911.000         115.000         104.000          84.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.251          -1.117*          0.113   \n                  (0.313)         (0.516)         (0.230)   \nwp_right2           0.897          -0.477          -0.181   \n                  (0.486)         (0.539)         (0.358)   \nc.neg#c.wp~2       -0.660           1.999          -0.240   \n                  (0.828)         (1.025)         (0.696)   \nvid_order          -0.105***       -0.105***       -0.040   \n                  (0.032)         (0.030)         (0.025)   \nfemale              0.095           0.018          -0.045   \n                  (0.159)         (0.134)         (0.114)   \nage                 0.008          -0.007          -0.001   \n                  (0.007)         (0.013)         (0.004)   \nincome              0.504           0.406           0.259   \n                  (0.460)         (0.329)         (0.255)   \nuniversity          0.389*          0.047          -0.012   \n                  (0.163)         (0.210)         (0.111)   \n_cons              -0.863*          0.573           0.044   \n                  (0.405)         (0.477)         (0.265)   \n------------------------------------------------------------\nr2_w                0.176           0.101           0.053   \nr2_b                0.243           0.142           0.012   \nr2_o                0.207           0.112           0.038   \nN                 113.000         179.000         107.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 13\" | v_negative==0) , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 13\" | v_negative==0) , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.217           0.200          -0.192   \n                  (0.397)         (0.247)         (0.338)   \nwp_right2          -0.141           0.120          -0.202   \n                  (0.490)         (0.210)         (0.263)   \nc.neg#c.wp~2       -0.682          -0.418           0.340   \n                  (1.006)         (0.383)         (0.517)   \nvid_order          -0.152***       -0.080***       -0.098***\n                  (0.036)         (0.015)         (0.022)   \nfemale             -0.173          -0.130*         -0.033   \n                  (0.156)         (0.063)         (0.095)   \nage                -0.007           0.001          -0.003   \n                  (0.008)         (0.003)         (0.007)   \nincome             -0.089           0.107           0.180   \n                  (0.374)         (0.127)         (0.197)   \nuniversity         -0.078          -0.030          -0.154   \n                  (0.152)         (0.066)         (0.111)   \n_cons               1.012*          0.172           0.508   \n                  (0.410)         (0.182)         (0.259)   \n------------------------------------------------------------\nr2_w                0.115           0.141           0.146   \nr2_b                0.138           0.187           0.091   \nr2_o                0.135           0.159           0.135   \nN                 151.000         190.000         159.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.251           0.329          -0.029   \n                  (0.279)         (0.434)         (0.200)   \nwp_right2          -0.190          -0.487           0.113   \n                  (0.504)         (0.448)         (0.314)   \nc.neg#c.wp~2        0.547          -0.500           0.189   \n                  (0.947)         (1.153)         (0.683)   \nvid_order          -0.175***       -0.085*         -0.059** \n                  (0.036)         (0.039)         (0.020)   \nfemale             -0.174           0.133          -0.200*  \n                  (0.149)         (0.169)         (0.096)   \nage                -0.009           0.002          -0.006   \n                  (0.026)         (0.045)         (0.009)   \nincome             -0.382          -0.027           0.351   \n                  (0.331)         (0.439)         (0.253)   \nuniversity         -0.450*         -0.087           0.249   \n                  (0.210)         (0.309)         (0.148)   \n_cons               1.518*          0.329           0.063   \n                  (0.771)         (1.012)         (0.372)   \n------------------------------------------------------------\nr2_w                0.089           0.080           0.093   \nr2_b                0.210           0.120           0.234   \nr2_o                0.132           0.099           0.129   \nN                 223.000         100.000         114.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_13\n> \" | v_negative==0) , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.010          -0.284          -0.179          -0.159   \n                  (0.556)         (0.227)         (0.408)         (0.189)   \nwp_right2           0.100           0.177           0.274          -0.026   \n                  (0.644)         (0.315)         (0.432)         (0.177)   \nc.neg#c.wp~2       -0.703           0.675           0.380           0.196   \n                  (1.384)         (0.603)         (0.681)         (0.307)   \nvid_order          -0.059          -0.083**        -0.071**        -0.028*  \n                  (0.044)         (0.027)         (0.028)         (0.012)   \nfemale              0.026           0.028           0.062           0.010   \n                  (0.194)         (0.121)         (0.176)         (0.057)   \nage                -0.059          -0.001           0.006           0.005   \n                  (0.061)         (0.003)         (0.009)         (0.003)   \nincome             -0.565           0.203          -0.232           0.016   \n                  (0.356)         (0.200)         (0.446)         (0.171)   \nuniversity          0.248           0.009          -0.020           0.023   \n                  (0.289)         (0.117)         (0.268)         (0.056)   \n_cons               1.462           0.111          -0.068          -0.031   \n                  (1.392)         (0.241)         (0.494)         (0.169)   \n----------------------------------------------------------------------------\nr2_w                0.065           0.102           0.081           0.062   \nr2_b                0.113           0.241           0.148           0.102   \nr2_o                0.086           0.124           0.106           0.077   \nN                 111.000         101.000          96.000         147.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.227          -0.547**        -0.170   \n                  (0.213)         (0.206)         (0.160)   \nwp_right2          -0.070          -0.344           0.108   \n                  (0.251)         (0.426)         (0.219)   \nc.neg#c.wp~2        0.163           1.315*          0.180   \n                  (0.513)         (0.554)         (0.379)   \nvid_order          -0.021          -0.090***       -0.054***\n                  (0.025)         (0.022)         (0.015)   \nfemale              0.201          -0.217          -0.042   \n                  (0.104)         (0.150)         (0.081)   \nage                 0.005          -0.000           0.005   \n                  (0.004)         (0.006)         (0.003)   \nincome             -0.397           0.229          -0.027   \n                  (0.267)         (0.301)         (0.158)   \nuniversity         -0.040          -0.128           0.084   \n                  (0.105)         (0.207)         (0.080)   \n_cons               0.075           0.516          -0.065   \n                  (0.244)         (0.307)         (0.185)   \n------------------------------------------------------------\nr2_w                0.060           0.144           0.039   \nr2_b                0.251           0.206           0.025   \nr2_o                0.104           0.178           0.033   \nN                 102.000         146.000         569.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negative\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 & (stimulus==\"v_14\" | v_negative==0\n> ) , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 14\" | v_negative==0) , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 14\" | v_negative==0) , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.184**         0.683           0.107          -0.028   \n                  (0.064)         (0.403)         (0.328)         (0.166)   \nwp_right2           0.022          -0.459          -0.459          -0.266   \n                  (0.071)         (0.422)         (0.726)         (0.314)   \nc.neg#c.wp~2        0.049          -0.860           1.403          -0.063   \n                  (0.142)         (0.978)         (1.053)         (0.542)   \nvid_order          -0.073***       -0.015          -0.106*         -0.045*  \n                  (0.007)         (0.037)         (0.045)         (0.022)   \nfemale             -0.009          -0.079           0.382           0.122   \n                  (0.029)         (0.150)         (0.293)         (0.151)   \nage                 0.001          -0.006           0.050          -0.004   \n                  (0.001)         (0.014)         (0.031)         (0.005)   \nincome             -0.016           0.201          -0.303           0.129   \n                  (0.061)         (0.338)         (0.503)         (0.296)   \nuniversity         -0.008           0.023          -0.246          -0.040   \n                  (0.031)         (0.155)         (0.398)         (0.153)   \n_cons               0.183**         0.292          -0.812           0.365   \n                  (0.070)         (0.452)         (0.920)         (0.324)   \n----------------------------------------------------------------------------\nr2_w                0.065           0.071           0.117           0.085   \nr2_b                0.035           0.091           0.249           0.078   \nr2_o                0.054           0.079           0.191           0.092   \nN                2886.000         105.000          98.000          80.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.204           0.408           0.228   \n                  (0.328)         (0.643)         (0.265)   \nwp_right2           0.454          -0.331          -0.008   \n                  (0.547)         (0.538)         (0.368)   \nc.neg#c.wp~2       -0.395          -0.286          -0.189   \n                  (0.831)         (1.225)         (0.726)   \nvid_order          -0.146***       -0.108***       -0.032   \n                  (0.034)         (0.030)         (0.025)   \nfemale              0.236          -0.055           0.065   \n                  (0.179)         (0.136)         (0.117)   \nage                 0.009          -0.006          -0.000   \n                  (0.008)         (0.013)         (0.004)   \nincome             -0.160           0.470           0.123   \n                  (0.532)         (0.315)         (0.259)   \nuniversity          0.331          -0.043           0.042   \n                  (0.182)         (0.210)         (0.115)   \n_cons              -0.357           0.569          -0.050   \n                  (0.464)         (0.481)         (0.281)   \n------------------------------------------------------------\nr2_w                0.208           0.087           0.045   \nr2_b                0.159           0.213           0.039   \nr2_o                0.189           0.114           0.043   \nN                 115.000         176.000         106.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 14\" | v_negative==0) , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_\n> 14\" | v_negative==0) , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.316           0.334           0.244   \n                  (0.337)         (0.268)         (0.327)   \nwp_right2          -0.085           0.096          -0.227   \n                  (0.491)         (0.247)         (0.263)   \nc.neg#c.wp~2       -0.133          -0.409           0.028   \n                  (0.835)         (0.414)         (0.504)   \nvid_order          -0.094**        -0.066***       -0.083***\n                  (0.033)         (0.015)         (0.022)   \nfemale             -0.040          -0.153          -0.052   \n                  (0.152)         (0.079)         (0.098)   \nage                -0.007           0.001          -0.000   \n                  (0.008)         (0.004)         (0.007)   \nincome              0.153           0.170           0.072   \n                  (0.363)         (0.156)         (0.202)   \nuniversity         -0.035          -0.028          -0.145   \n                  (0.151)         (0.083)         (0.113)   \n_cons               0.509           0.115           0.422   \n                  (0.404)         (0.215)         (0.262)   \n------------------------------------------------------------\nr2_w                0.099           0.121           0.124   \nr2_b                0.046           0.154           0.140   \nr2_o                0.088           0.148           0.134   \nN                 161.000         186.000         156.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.025          -0.141           0.166   \n                  (0.261)         (0.468)         (0.173)   \nwp_right2          -0.190          -0.527           0.093   \n                  (0.527)         (0.488)         (0.302)   \nc.neg#c.wp~2        0.424           0.912          -0.152   \n                  (0.916)         (1.131)         (0.663)   \nvid_order          -0.163***       -0.075          -0.048*  \n                  (0.034)         (0.042)         (0.019)   \nfemale             -0.215           0.247          -0.149   \n                  (0.158)         (0.181)         (0.089)   \nage                -0.023           0.004          -0.005   \n                  (0.028)         (0.048)         (0.009)   \nincome             -0.482          -0.238           0.341   \n                  (0.355)         (0.450)         (0.246)   \nuniversity         -0.269          -0.075           0.149   \n                  (0.226)         (0.318)         (0.140)   \n_cons               1.741*          0.285           0.043   \n                  (0.819)         (1.049)         (0.351)   \n------------------------------------------------------------\nr2_w                0.089           0.044           0.126   \nr2_b                0.241           0.180           0.058   \nr2_o                0.135           0.079           0.104   \nN                 226.000         103.000         116.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 & (stimulus==\"v_14\n> \" | v_negative==0) , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.451          -0.428          -0.284           0.219   \n                  (0.453)         (0.239)         (0.339)         (0.231)   \nwp_right2           0.169           0.104           0.279          -0.101   \n                  (0.666)         (0.318)         (0.427)         (0.207)   \nc.neg#c.wp~2       -0.266           1.239*          0.747          -0.216   \n                  (1.143)         (0.610)         (0.558)         (0.366)   \nvid_order          -0.084          -0.080**        -0.058          -0.031*  \n                  (0.044)         (0.025)         (0.031)         (0.013)   \nfemale              0.039          -0.018           0.240           0.057   \n                  (0.197)         (0.123)         (0.169)         (0.071)   \nage                -0.055          -0.003           0.006           0.005   \n                  (0.064)         (0.003)         (0.009)         (0.003)   \nincome             -0.526           0.026          -0.325           0.170   \n                  (0.348)         (0.208)         (0.437)         (0.209)   \nuniversity         -0.023           0.086          -0.023           0.009   \n                  (0.306)         (0.121)         (0.258)         (0.068)   \n_cons               1.662           0.282          -0.160          -0.047   \n                  (1.456)         (0.242)         (0.491)         (0.192)   \n----------------------------------------------------------------------------\nr2_w                0.060           0.134           0.076           0.066   \nr2_b                0.179           0.224           0.260           0.132   \nr2_o                0.096           0.157           0.160           0.097   \nN                 113.000         100.000          98.000         140.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.216           0.146           0.385*  \n                  (0.222)         (0.219)         (0.175)   \nwp_right2          -0.006          -0.249           0.115   \n                  (0.251)         (0.429)         (0.212)   \nc.neg#c.wp~2        0.810           0.378          -0.231   \n                  (0.652)         (0.645)         (0.407)   \nvid_order          -0.022          -0.082**        -0.036*  \n                  (0.025)         (0.027)         (0.015)   \nfemale              0.164          -0.134           0.006   \n                  (0.104)         (0.150)         (0.077)   \nage                 0.002          -0.001           0.004   \n                  (0.004)         (0.006)         (0.003)   \nincome             -0.448          -0.068          -0.006   \n                  (0.276)         (0.301)         (0.151)   \nuniversity          0.016          -0.181           0.081   \n                  (0.108)         (0.203)         (0.078)   \n_cons               0.219           0.596          -0.144   \n                  (0.247)         (0.313)         (0.179)   \n------------------------------------------------------------\nr2_w                0.033           0.102           0.054   \nr2_b                0.239           0.132           0.013   \nr2_o                0.085           0.106           0.035   \nN                  97.000         146.000         564.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.         \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(56,936 real changes made, 39,228 to missing)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_1202\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_1202\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.101**        -0.299          -0.042   \n                  (0.032)         (0.179)         (0.127)   \nwp_right2           0.027          -0.062           0.081   \n                  (0.021)         (0.138)         (0.129)   \nc.neg#c.wp~2       -0.128           1.102*          0.364   \n                  (0.070)         (0.436)         (0.384)   \npho_order           0.004***        0.011***        0.009** \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.001           0.007           0.110   \n                  (0.009)         (0.051)         (0.063)   \nage                -0.000           0.004           0.000   \n                  (0.000)         (0.005)         (0.002)   \nincome              0.003          -0.087          -0.109   \n                  (0.019)         (0.110)         (0.122)   \nuniversity          0.006           0.020           0.140*  \n                  (0.009)         (0.051)         (0.065)   \n_cons              -0.076***       -0.235          -0.258   \n                  (0.022)         (0.148)         (0.138)   \n------------------------------------------------------------\nr2_w                0.005           0.055           0.027   \nr2_b                0.017           0.075           0.283   \nr2_o                0.005           0.055           0.054   \nN                8834.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.157          -0.108           0.139   \n                  (0.154)         (0.226)         (0.077)   \nwp_right2          -0.279*          0.013           0.035   \n                  (0.142)         (0.159)         (0.099)   \nc.neg#c.wp~2        0.772           0.232          -0.282   \n                  (0.415)         (0.442)         (0.227)   \npho_order           0.005           0.003           0.004*  \n                  (0.003)         (0.003)         (0.002)   \nfemale              0.049           0.002          -0.026   \n                  (0.050)         (0.043)         (0.034)   \nage                -0.001          -0.003           0.001   \n                  (0.002)         (0.004)         (0.001)   \nincome             -0.051           0.089           0.011   \n                  (0.144)         (0.112)         (0.072)   \nuniversity         -0.069          -0.001           0.018   \n                  (0.051)         (0.062)         (0.033)   \n_cons               0.075          -0.029          -0.126   \n                  (0.129)         (0.146)         (0.075)   \n------------------------------------------------------------\nr2_w                0.019           0.002           0.027   \nr2_b                0.139           0.025           0.058   \nr2_o                0.028           0.005           0.031   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_1202\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_1202\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.146           0.008           0.456*          0.090   \n                  (0.142)         (0.154)         (0.178)         (0.136)   \nwp_right2           0.137          -0.025           0.083           0.286   \n                  (0.120)         (0.089)         (0.090)         (0.206)   \nc.neg#c.wp~2       -0.184          -0.087          -0.706*         -0.222   \n                  (0.356)         (0.236)         (0.275)         (0.380)   \npho_order           0.007**         0.004*          0.003           0.003   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale             -0.006           0.012          -0.006           0.034   \n                  (0.038)         (0.030)         (0.034)         (0.070)   \nage                 0.001          -0.001          -0.001           0.007   \n                  (0.002)         (0.001)         (0.002)         (0.009)   \nincome             -0.076          -0.002           0.032          -0.005   \n                  (0.092)         (0.059)         (0.075)         (0.141)   \nuniversity          0.048          -0.007          -0.010          -0.029   \n                  (0.038)         (0.031)         (0.040)         (0.099)   \n_cons              -0.227*         -0.016          -0.077          -0.266   \n                  (0.099)         (0.079)         (0.095)         (0.291)   \n----------------------------------------------------------------------------\nr2_w                0.016           0.008           0.018           0.005   \nr2_b                0.227           0.035           0.005           0.139   \nr2_o                0.027           0.011           0.017           0.022   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.250           0.038           0.174   \n                  (0.206)         (0.094)         (0.242)   \nwp_right2          -0.093          -0.013          -0.092   \n                  (0.170)         (0.102)         (0.214)   \nc.neg#c.wp~2        0.369           0.219          -0.246   \n                  (0.507)         (0.330)         (0.625)   \npho_order           0.011**         0.005**        -0.006   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.134*         -0.032          -0.046   \n                  (0.066)         (0.032)         (0.065)   \nage                 0.026          -0.002          -0.009   \n                  (0.017)         (0.003)         (0.021)   \nincome              0.002           0.034           0.156   \n                  (0.158)         (0.089)         (0.126)   \nuniversity          0.078          -0.013           0.007   \n                  (0.178)         (0.048)         (0.102)   \n_cons              -0.603          -0.009           0.260   \n                  (0.371)         (0.118)         (0.491)   \n------------------------------------------------------------\nr2_w                0.025           0.031           0.012   \nr2_b                0.278           0.042           0.077   \nr2_o                0.055           0.032           0.015   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_1202\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.348**        -0.167           0.122   \n                  (0.122)         (0.176)         (0.110)   \nwp_right2           0.030           0.148          -0.039   \n                  (0.120)         (0.091)         (0.057)   \nc.neg#c.wp~2       -0.682*          0.360          -0.128   \n                  (0.322)         (0.289)         (0.175)   \npho_order           0.001          -0.000           0.001   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.030          -0.043           0.031   \n                  (0.048)         (0.038)         (0.020)   \nage                 0.001          -0.002           0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.042           0.025          -0.050   \n                  (0.076)         (0.096)         (0.059)   \nuniversity          0.011          -0.080          -0.008   \n                  (0.046)         (0.058)         (0.019)   \n_cons              -0.108           0.030           0.017   \n                  (0.094)         (0.110)         (0.056)   \n------------------------------------------------------------\nr2_w                0.026           0.006           0.006   \nr2_b                0.079           0.266           0.172   \nr2_o                0.032           0.027           0.014   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.386***        0.034           0.197   \n                  (0.102)         (0.130)         (0.108)   \nwp_right2          -0.113           0.047           0.054   \n                  (0.117)         (0.123)         (0.085)   \nc.neg#c.wp~2       -0.690**        -0.043          -0.341   \n                  (0.258)         (0.369)         (0.273)   \npho_order           0.003           0.003           0.002   \n                  (0.002)         (0.003)         (0.002)   \nfemale              0.017           0.032          -0.002   \n                  (0.053)         (0.044)         (0.028)   \nage                 0.004*         -0.002          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.094          -0.111           0.112   \n                  (0.136)         (0.088)         (0.058)   \nuniversity          0.003          -0.067           0.037   \n                  (0.054)         (0.060)         (0.029)   \n_cons              -0.312**         0.073          -0.131   \n                  (0.116)         (0.094)         (0.068)   \n------------------------------------------------------------\nr2_w                0.048           0.002           0.004   \nr2_b                0.216           0.104           0.049   \nr2_o                0.081           0.012           0.008   \nN                 338.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                 \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_2683\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_2683\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.014          -0.036           0.165   \n                  (0.032)         (0.167)         (0.133)   \nwp_right2           0.027          -0.062           0.095   \n                  (0.021)         (0.129)         (0.170)   \nc.neg#c.wp~2       -0.036          -0.148          -0.626   \n                  (0.069)         (0.406)         (0.400)   \npho_order           0.004***        0.009**         0.008*  \n                  (0.001)         (0.003)         (0.004)   \nfemale              0.000           0.018           0.131   \n                  (0.009)         (0.047)         (0.085)   \nage                -0.000          -0.001           0.001   \n                  (0.000)         (0.005)         (0.003)   \nincome             -0.001          -0.076          -0.137   \n                  (0.019)         (0.102)         (0.164)   \nuniversity          0.008           0.015           0.184*  \n                  (0.009)         (0.048)         (0.088)   \n_cons              -0.077***       -0.118          -0.295   \n                  (0.021)         (0.138)         (0.179)   \n------------------------------------------------------------\nr2_w                0.005           0.037           0.030   \nr2_b                0.009           0.042           0.255   \nr2_o                0.005           0.037           0.066   \nN                8835.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.153           0.017          -0.050   \n                  (0.147)         (0.230)         (0.069)   \nwp_right2          -0.244           0.062           0.014   \n                  (0.146)         (0.153)         (0.117)   \nc.neg#c.wp~2        0.160          -0.117           0.144   \n                  (0.397)         (0.450)         (0.203)   \npho_order           0.006           0.001           0.004** \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.053          -0.025          -0.033   \n                  (0.052)         (0.041)         (0.040)   \nage                -0.001          -0.001           0.001   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.039           0.043           0.035   \n                  (0.150)         (0.107)         (0.085)   \nuniversity         -0.062           0.005           0.000   \n                  (0.053)         (0.060)         (0.040)   \n_cons               0.002          -0.041          -0.131   \n                  (0.131)         (0.141)         (0.087)   \n------------------------------------------------------------\nr2_w                0.017           0.001           0.022   \nr2_b                0.128           0.028           0.087   \nr2_o                0.028           0.002           0.036   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_2683\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_2683\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.070           0.167           0.151          -0.067   \n                  (0.138)         (0.156)         (0.169)         (0.132)   \nwp_right2           0.116          -0.022           0.087           0.354   \n                  (0.116)         (0.086)         (0.086)         (0.204)   \nc.neg#c.wp~2       -0.214          -0.263          -0.371          -0.122   \n                  (0.344)         (0.239)         (0.261)         (0.370)   \npho_order           0.009***        0.004*          0.002           0.004   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale              0.012           0.024           0.015           0.055   \n                  (0.037)         (0.029)         (0.033)         (0.069)   \nage                 0.002          -0.001          -0.002           0.011   \n                  (0.002)         (0.001)         (0.002)         (0.009)   \nincome             -0.089          -0.013          -0.015           0.061   \n                  (0.089)         (0.057)         (0.072)         (0.140)   \nuniversity          0.055          -0.003           0.019          -0.044   \n                  (0.037)         (0.030)         (0.038)         (0.098)   \n_cons              -0.264**        -0.010          -0.039          -0.424   \n                  (0.096)         (0.077)         (0.091)         (0.286)   \n----------------------------------------------------------------------------\nr2_w                0.022           0.010           0.011           0.015   \nr2_b                0.236           0.050           0.027           0.203   \nr2_o                0.034           0.015           0.012           0.042   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.105          -0.027          -0.291   \n                  (0.206)         (0.090)         (0.239)   \nwp_right2          -0.089          -0.027          -0.187   \n                  (0.174)         (0.098)         (0.212)   \nc.neg#c.wp~2        0.317           0.190           1.036   \n                  (0.506)         (0.318)         (0.617)   \npho_order           0.010**         0.005**        -0.002   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.103          -0.069*         -0.112   \n                  (0.067)         (0.031)         (0.065)   \nage                 0.023          -0.005          -0.022   \n                  (0.017)         (0.003)         (0.021)   \nincome              0.044           0.081           0.099   \n                  (0.162)         (0.086)         (0.125)   \nuniversity          0.120           0.028           0.007   \n                  (0.181)         (0.047)         (0.100)   \n_cons              -0.610           0.024           0.570   \n                  (0.380)         (0.114)         (0.483)   \n------------------------------------------------------------\nr2_w                0.017           0.024           0.010   \nr2_b                0.221           0.237           0.159   \nr2_o                0.040           0.038           0.022   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_2683\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.076          -0.161           0.058   \n                  (0.117)         (0.165)         (0.103)   \nwp_right2           0.012           0.141          -0.026   \n                  (0.115)         (0.086)         (0.054)   \nc.neg#c.wp~2       -0.051           0.191          -0.159   \n                  (0.307)         (0.271)         (0.165)   \npho_order           0.004           0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.018          -0.048           0.018   \n                  (0.046)         (0.035)         (0.018)   \nage                 0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.039           0.011          -0.065   \n                  (0.073)         (0.090)         (0.056)   \nuniversity          0.029          -0.092          -0.005   \n                  (0.044)         (0.054)         (0.018)   \n_cons              -0.137           0.020           0.034   \n                  (0.090)         (0.103)         (0.053)   \n------------------------------------------------------------\nr2_w                0.004           0.004           0.007   \nr2_b                0.135           0.319           0.126   \nr2_o                0.016           0.029           0.013   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.070          -0.046          -0.109   \n                  (0.096)         (0.129)         (0.106)   \nwp_right2          -0.125           0.048           0.059   \n                  (0.104)         (0.121)         (0.084)   \nc.neg#c.wp~2       -0.121           0.089           0.103   \n                  (0.243)         (0.365)         (0.268)   \npho_order           0.002           0.003           0.003   \n                  (0.002)         (0.003)         (0.002)   \nfemale             -0.021           0.029           0.011   \n                  (0.047)         (0.043)         (0.028)   \nage                 0.004*         -0.002          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.137          -0.135           0.116*  \n                  (0.120)         (0.086)         (0.057)   \nuniversity         -0.035          -0.029           0.040   \n                  (0.048)         (0.059)         (0.029)   \n_cons              -0.249*          0.066          -0.149*  \n                  (0.104)         (0.093)         (0.067)   \n------------------------------------------------------------\nr2_w                0.004           0.002           0.004   \nr2_b                0.266           0.092           0.059   \nr2_o                0.043           0.010           0.008   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                 \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_3530\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_3530\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.018          -0.095          -0.084   \n                  (0.032)         (0.165)         (0.127)   \nwp_right2           0.024          -0.071           0.072   \n                  (0.021)         (0.128)         (0.131)   \nc.neg#c.wp~2       -0.058           0.099           0.994** \n                  (0.069)         (0.400)         (0.383)   \npho_order           0.004***        0.011***        0.007*  \n                  (0.001)         (0.003)         (0.003)   \nfemale             -0.003           0.019           0.098   \n                  (0.009)         (0.047)         (0.064)   \nage                -0.000          -0.002           0.000   \n                  (0.000)         (0.005)         (0.002)   \nincome             -0.017          -0.034          -0.158   \n                  (0.019)         (0.102)         (0.124)   \nuniversity          0.003           0.013           0.143*  \n                  (0.009)         (0.048)         (0.067)   \n_cons              -0.065**        -0.119          -0.205   \n                  (0.022)         (0.136)         (0.141)   \n------------------------------------------------------------\nr2_w                0.004           0.040           0.056   \nr2_b                0.012           0.060           0.295   \nr2_o                0.004           0.042           0.082   \nN                8835.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009           0.317          -0.025   \n                  (0.154)         (0.228)         (0.069)   \nwp_right2          -0.261           0.052           0.028   \n                  (0.163)         (0.152)         (0.119)   \nc.neg#c.wp~2       -0.308          -0.714           0.018   \n                  (0.416)         (0.445)         (0.204)   \npho_order           0.004           0.001           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.040          -0.008          -0.027   \n                  (0.058)         (0.041)         (0.041)   \nage                -0.001          -0.000           0.001   \n                  (0.002)         (0.004)         (0.001)   \nincome             -0.011          -0.028           0.021   \n                  (0.167)         (0.106)         (0.087)   \nuniversity         -0.071           0.009           0.010   \n                  (0.059)         (0.059)         (0.041)   \n_cons               0.066          -0.039          -0.129   \n                  (0.146)         (0.140)         (0.089)   \n------------------------------------------------------------\nr2_w                0.010           0.005           0.014   \nr2_b                0.120           0.008           0.069   \nr2_o                0.023           0.005           0.026   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_3530\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_3530\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.009          -0.039           0.026           0.171   \n                  (0.140)         (0.158)         (0.177)         (0.146)   \nwp_right2           0.109          -0.020           0.073           0.262   \n                  (0.118)         (0.084)         (0.089)         (0.167)   \nc.neg#c.wp~2        0.162           0.072          -0.013          -0.636   \n                  (0.350)         (0.242)         (0.275)         (0.409)   \npho_order           0.008**         0.004*          0.002           0.003   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale              0.017           0.024           0.007           0.032   \n                  (0.037)         (0.028)         (0.034)         (0.056)   \nage                 0.002          -0.000          -0.002           0.003   \n                  (0.002)         (0.001)         (0.002)         (0.007)   \nincome             -0.120          -0.011          -0.001           0.064   \n                  (0.090)         (0.055)         (0.075)         (0.113)   \nuniversity          0.062          -0.025          -0.004          -0.039   \n                  (0.037)         (0.030)         (0.040)         (0.079)   \n_cons              -0.238*         -0.032          -0.014          -0.195   \n                  (0.097)         (0.076)         (0.095)         (0.234)   \n----------------------------------------------------------------------------\nr2_w                0.022           0.006           0.003           0.012   \nr2_b                0.306           0.062           0.035           0.147   \nr2_o                0.038           0.012           0.005           0.023   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.270          -0.028           0.003   \n                  (0.207)         (0.085)         (0.238)   \nwp_right2          -0.103          -0.032          -0.158   \n                  (0.160)         (0.093)         (0.210)   \nc.neg#c.wp~2        0.357           0.169          -0.006   \n                  (0.508)         (0.301)         (0.612)   \npho_order           0.012**         0.006**        -0.004   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.124*         -0.069*         -0.081   \n                  (0.062)         (0.029)         (0.064)   \nage                 0.021          -0.005*         -0.018   \n                  (0.016)         (0.002)         (0.021)   \nincome             -0.039           0.035           0.092   \n                  (0.148)         (0.081)         (0.124)   \nuniversity          0.068          -0.011           0.017   \n                  (0.166)         (0.044)         (0.099)   \n_cons              -0.501           0.102           0.474   \n                  (0.347)         (0.108)         (0.479)   \n------------------------------------------------------------\nr2_w                0.027           0.028           0.005   \nr2_b                0.270           0.209           0.110   \nr2_o                0.052           0.042           0.011   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_3530\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.207           0.881***        0.018   \n                  (0.120)         (0.169)         (0.104)   \nwp_right2           0.023           0.151          -0.040   \n                  (0.118)         (0.088)         (0.054)   \nc.neg#c.wp~2       -0.378          -1.281***        0.004   \n                  (0.317)         (0.277)         (0.166)   \npho_order           0.003           0.003           0.001   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.016          -0.070           0.034   \n                  (0.048)         (0.036)         (0.018)   \nage                 0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.017           0.045          -0.063   \n                  (0.075)         (0.092)         (0.056)   \nuniversity          0.011          -0.069          -0.013   \n                  (0.046)         (0.056)         (0.018)   \n_cons              -0.128          -0.027           0.040   \n                  (0.093)         (0.106)         (0.053)   \n------------------------------------------------------------\nr2_w                0.011           0.080           0.002   \nr2_b                0.079           0.338           0.226   \nr2_o                0.016           0.094           0.012   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.081          -0.011           0.025   \n                  (0.092)         (0.128)         (0.108)   \nwp_right2          -0.143           0.047           0.050   \n                  (0.118)         (0.116)         (0.085)   \nc.neg#c.wp~2       -0.181           0.009          -0.277   \n                  (0.234)         (0.363)         (0.274)   \npho_order           0.001           0.004           0.003   \n                  (0.002)         (0.003)         (0.002)   \nfemale             -0.016           0.032          -0.001   \n                  (0.054)         (0.041)         (0.028)   \nage                 0.005*         -0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.131          -0.126           0.079   \n                  (0.137)         (0.083)         (0.058)   \nuniversity         -0.035          -0.040           0.027   \n                  (0.055)         (0.056)         (0.029)   \n_cons              -0.283*          0.052          -0.127   \n                  (0.117)         (0.090)         (0.068)   \n------------------------------------------------------------\nr2_w                0.004           0.003           0.004   \nr2_b                0.278           0.117           0.029   \nr2_o                0.059           0.011           0.006   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                 \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_6260\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_6260\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.182***        0.281           0.178   \n                  (0.033)         (0.173)         (0.129)   \nwp_right2           0.027          -0.042           0.098   \n                  (0.022)         (0.133)         (0.154)   \nc.neg#c.wp~2       -0.116          -0.183          -0.328   \n                  (0.071)         (0.425)         (0.392)   \npho_order           0.004***        0.010**         0.009** \n                  (0.001)         (0.003)         (0.003)   \nfemale             -0.002          -0.025           0.134   \n                  (0.009)         (0.049)         (0.076)   \nage                -0.000           0.001           0.001   \n                  (0.000)         (0.005)         (0.003)   \nincome             -0.005          -0.080          -0.197   \n                  (0.020)         (0.106)         (0.148)   \nuniversity          0.007           0.018           0.200*  \n                  (0.010)         (0.049)         (0.079)   \n_cons              -0.062**        -0.138          -0.298   \n                  (0.022)         (0.143)         (0.163)   \n------------------------------------------------------------\nr2_w                0.012           0.055           0.030   \nr2_b                0.010           0.059           0.342   \nr2_o                0.012           0.055           0.078   \nN                8834.000         360.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.138          -0.191           0.157*  \n                  (0.161)         (0.251)         (0.075)   \nwp_right2          -0.182           0.029           0.014   \n                  (0.149)         (0.173)         (0.117)   \nc.neg#c.wp~2        0.270           0.938          -0.086   \n                  (0.437)         (0.491)         (0.221)   \npho_order           0.003           0.001           0.003   \n                  (0.003)         (0.004)         (0.002)   \nfemale              0.007           0.004          -0.045   \n                  (0.053)         (0.047)         (0.040)   \nage                -0.003          -0.001           0.000   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.195           0.070           0.021   \n                  (0.152)         (0.121)         (0.085)   \nuniversity         -0.050          -0.011           0.014   \n                  (0.054)         (0.068)         (0.040)   \n_cons               0.058          -0.053          -0.095   \n                  (0.136)         (0.160)         (0.088)   \n------------------------------------------------------------\nr2_w                0.021           0.035           0.041   \nr2_b                0.191           0.022           0.086   \nr2_o                0.033           0.034           0.049   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_6260\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_6260\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.321*          0.074           0.174           0.058   \n                  (0.142)         (0.157)         (0.174)         (0.138)   \nwp_right2           0.157          -0.015           0.098           0.289   \n                  (0.120)         (0.095)         (0.088)         (0.208)   \nc.neg#c.wp~2       -0.211          -0.026          -0.332          -0.126   \n                  (0.356)         (0.241)         (0.269)         (0.385)   \npho_order           0.009***        0.003           0.002           0.002   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale             -0.006           0.017           0.013           0.029   \n                  (0.038)         (0.032)         (0.034)         (0.071)   \nage                 0.000          -0.002          -0.002           0.008   \n                  (0.002)         (0.002)         (0.002)         (0.009)   \nincome             -0.104          -0.012          -0.019          -0.045   \n                  (0.092)         (0.063)         (0.074)         (0.143)   \nuniversity          0.049          -0.010           0.035          -0.019   \n                  (0.038)         (0.034)         (0.039)         (0.100)   \n_cons              -0.206*          0.015          -0.031          -0.267   \n                  (0.099)         (0.085)         (0.093)         (0.291)   \n----------------------------------------------------------------------------\nr2_w                0.049           0.009           0.006           0.001   \nr2_b                0.232           0.033           0.049           0.156   \nr2_o                0.057           0.012           0.009           0.022   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.209           0.163          -0.059   \n                  (0.210)         (0.090)         (0.247)   \nwp_right2          -0.101          -0.023          -0.105   \n                  (0.159)         (0.099)         (0.218)   \nc.neg#c.wp~2        0.244          -0.359           0.314   \n                  (0.515)         (0.318)         (0.637)   \npho_order           0.010**         0.005**        -0.003   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.126*         -0.067*         -0.063   \n                  (0.061)         (0.031)         (0.066)   \nage                 0.023          -0.004          -0.008   \n                  (0.016)         (0.003)         (0.021)   \nincome             -0.046           0.033           0.119   \n                  (0.147)         (0.086)         (0.128)   \nuniversity          0.151          -0.012          -0.096   \n                  (0.165)         (0.047)         (0.103)   \n_cons              -0.580           0.066           0.309   \n                  (0.346)         (0.115)         (0.499)   \n------------------------------------------------------------\nr2_w                0.022           0.032           0.002   \nr2_b                0.365           0.149           0.177   \nr2_o                0.055           0.040           0.012   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_6260\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.727***        0.590***        0.137   \n                  (0.131)         (0.178)         (0.103)   \nwp_right2           0.014           0.157          -0.036   \n                  (0.128)         (0.093)         (0.054)   \nc.neg#c.wp~2       -1.174***       -0.546          -0.163   \n                  (0.344)         (0.293)         (0.165)   \npho_order           0.002           0.002           0.001   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.009          -0.057           0.026   \n                  (0.052)         (0.038)         (0.018)   \nage                 0.000          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.041           0.010          -0.046   \n                  (0.082)         (0.097)         (0.056)   \nuniversity          0.034          -0.075          -0.006   \n                  (0.050)         (0.059)         (0.018)   \n_cons              -0.094           0.020           0.039   \n                  (0.101)         (0.113)         (0.053)   \n------------------------------------------------------------\nr2_w                0.107           0.063           0.006   \nr2_b                0.074           0.306           0.121   \nr2_o                0.104           0.077           0.014   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.208*          0.087           0.142   \n                  (0.106)         (0.131)         (0.107)   \nwp_right2          -0.103           0.046           0.058   \n                  (0.116)         (0.119)         (0.085)   \nc.neg#c.wp~2        0.124          -0.133           0.061   \n                  (0.268)         (0.372)         (0.272)   \npho_order           0.000           0.003           0.002   \n                  (0.003)         (0.003)         (0.002)   \nfemale              0.023           0.049           0.000   \n                  (0.052)         (0.042)         (0.028)   \nage                 0.004*         -0.001          -0.002   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.080          -0.129           0.107   \n                  (0.134)         (0.085)         (0.059)   \nuniversity         -0.013          -0.044           0.027   \n                  (0.053)         (0.058)         (0.029)   \n_cons              -0.253*          0.046          -0.110   \n                  (0.115)         (0.092)         (0.069)   \n------------------------------------------------------------\nr2_w                0.051           0.003           0.010   \nr2_b                0.193           0.137           0.053   \nr2_o                0.070           0.013           0.014   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                 \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_6510\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_6510\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.065*         -0.150           0.046   \n                  (0.032)         (0.167)         (0.129)   \nwp_right2           0.027          -0.070           0.081   \n                  (0.021)         (0.129)         (0.138)   \nc.neg#c.wp~2       -0.062           0.722          -0.127   \n                  (0.070)         (0.406)         (0.390)   \npho_order           0.004***        0.010***        0.008*  \n                  (0.001)         (0.003)         (0.004)   \nfemale             -0.001           0.003           0.112   \n                  (0.009)         (0.047)         (0.068)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.005)         (0.002)   \nincome             -0.001          -0.029          -0.083   \n                  (0.019)         (0.103)         (0.132)   \nuniversity          0.006           0.022           0.130   \n                  (0.009)         (0.048)         (0.071)   \n_cons              -0.067**        -0.153          -0.263   \n                  (0.022)         (0.138)         (0.148)   \n------------------------------------------------------------\nr2_w                0.004           0.050           0.021   \nr2_b                0.011           0.021           0.219   \nr2_o                0.005           0.048           0.043   \nN                8835.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.164          -0.034           0.004   \n                  (0.151)         (0.228)         (0.069)   \nwp_right2          -0.259           0.059           0.005   \n                  (0.140)         (0.152)         (0.127)   \nc.neg#c.wp~2        0.399           0.121          -0.010   \n                  (0.407)         (0.445)         (0.206)   \npho_order           0.005           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.042          -0.018          -0.042   \n                  (0.049)         (0.041)         (0.044)   \nage                -0.001          -0.003           0.001   \n                  (0.002)         (0.004)         (0.001)   \nincome             -0.012          -0.002           0.047   \n                  (0.142)         (0.106)         (0.093)   \nuniversity         -0.068           0.003           0.009   \n                  (0.050)         (0.059)         (0.043)   \n_cons               0.050           0.001          -0.133   \n                  (0.128)         (0.140)         (0.095)   \n------------------------------------------------------------\nr2_w                0.012           0.001           0.014   \nr2_b                0.126           0.016           0.080   \nr2_o                0.022           0.002           0.030   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_6510\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_6510\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.181           0.184          -0.111          -0.030   \n                  (0.139)         (0.156)         (0.168)         (0.134)   \nwp_right2           0.131          -0.023           0.079           0.282   \n                  (0.118)         (0.096)         (0.085)         (0.208)   \nc.neg#c.wp~2       -0.114          -0.251           0.103           0.187   \n                  (0.349)         (0.240)         (0.260)         (0.374)   \npho_order           0.007**         0.004*          0.003           0.003   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale              0.007           0.020           0.021           0.042   \n                  (0.037)         (0.033)         (0.033)         (0.071)   \nage                 0.001          -0.001          -0.001           0.008   \n                  (0.002)         (0.002)         (0.002)         (0.009)   \nincome             -0.122           0.016           0.004          -0.001   \n                  (0.090)         (0.064)         (0.071)         (0.142)   \nuniversity          0.058          -0.002           0.002          -0.047   \n                  (0.037)         (0.034)         (0.038)         (0.100)   \n_cons              -0.193*         -0.018          -0.056          -0.266   \n                  (0.097)         (0.086)         (0.090)         (0.292)   \n----------------------------------------------------------------------------\nr2_w                0.023           0.011           0.006           0.005   \nr2_b                0.222           0.049           0.044           0.183   \nr2_o                0.034           0.016           0.008           0.031   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.067           0.011           0.330   \n                  (0.212)         (0.092)         (0.237)   \nwp_right2          -0.105          -0.009          -0.124   \n                  (0.168)         (0.101)         (0.210)   \nc.neg#c.wp~2       -0.530          -0.056          -0.608   \n                  (0.525)         (0.325)         (0.612)   \npho_order           0.012**         0.005*         -0.003   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.113          -0.047          -0.068   \n                  (0.065)         (0.032)         (0.064)   \nage                 0.021          -0.004          -0.014   \n                  (0.016)         (0.003)         (0.021)   \nincome             -0.069           0.004           0.137   \n                  (0.155)         (0.088)         (0.124)   \nuniversity          0.109           0.032          -0.029   \n                  (0.174)         (0.048)         (0.100)   \n_cons              -0.535           0.039           0.380   \n                  (0.364)         (0.117)         (0.478)   \n------------------------------------------------------------\nr2_w                0.023           0.019           0.008   \nr2_b                0.302           0.099           0.160   \nr2_o                0.058           0.024           0.018   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_6510\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.305*          0.072          -0.198   \n                  (0.119)         (0.161)         (0.102)   \nwp_right2           0.026           0.148          -0.031   \n                  (0.122)         (0.084)         (0.054)   \nc.neg#c.wp~2       -0.664*         -0.155           0.320   \n                  (0.313)         (0.264)         (0.164)   \npho_order           0.003           0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.020          -0.060           0.022   \n                  (0.049)         (0.035)         (0.018)   \nage                 0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.010           0.004          -0.031   \n                  (0.078)         (0.088)         (0.055)   \nuniversity          0.007          -0.079           0.006   \n                  (0.047)         (0.053)         (0.018)   \n_cons              -0.138           0.018           0.020   \n                  (0.095)         (0.101)         (0.052)   \n------------------------------------------------------------\nr2_w                0.021           0.001           0.009   \nr2_b                0.075           0.315           0.110   \nr2_o                0.026           0.025           0.012   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.143           0.044           0.071   \n                  (0.094)         (0.129)         (0.110)   \nwp_right2          -0.122           0.049           0.061   \n                  (0.120)         (0.117)         (0.087)   \nc.neg#c.wp~2       -0.075           0.149           0.027   \n                  (0.239)         (0.366)         (0.279)   \npho_order           0.002           0.003           0.001   \n                  (0.002)         (0.003)         (0.002)   \nfemale             -0.001           0.029          -0.013   \n                  (0.055)         (0.042)         (0.029)   \nage                 0.004*         -0.002          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.101          -0.133           0.095   \n                  (0.140)         (0.083)         (0.060)   \nuniversity         -0.011          -0.027           0.042   \n                  (0.056)         (0.057)         (0.030)   \n_cons              -0.276*          0.060          -0.092   \n                  (0.118)         (0.091)         (0.070)   \n------------------------------------------------------------\nr2_w                0.018           0.005           0.002   \nr2_b                0.210           0.119           0.050   \nr2_o                0.053           0.014           0.006   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                  \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_3059\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_3059\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.091**         0.151           0.018   \n                  (0.033)         (0.167)         (0.132)   \nwp_right2           0.027          -0.052           0.075   \n                  (0.022)         (0.138)         (0.125)   \nc.neg#c.wp~2       -0.013          -0.283           0.564   \n                  (0.071)         (0.406)         (0.398)   \npho_order           0.003***        0.009**         0.008*  \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.002          -0.011           0.106   \n                  (0.009)         (0.051)         (0.061)   \nage                -0.000          -0.001          -0.000   \n                  (0.000)         (0.005)         (0.002)   \nincome             -0.006          -0.016          -0.144   \n                  (0.020)         (0.111)         (0.118)   \nuniversity          0.005          -0.006           0.121   \n                  (0.010)         (0.051)         (0.063)   \n_cons              -0.052*         -0.097          -0.195   \n                  (0.023)         (0.148)         (0.135)   \n------------------------------------------------------------\nr2_w                0.006           0.031           0.042   \nr2_b                0.007           0.051           0.266   \nr2_o                0.006           0.032           0.061   \nN                8834.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.247          -0.334          -0.094   \n                  (0.149)         (0.261)         (0.079)   \nwp_right2          -0.263          -0.016           0.023   \n                  (0.150)         (0.174)         (0.118)   \nc.neg#c.wp~2       -0.562           0.956           0.674** \n                  (0.403)         (0.510)         (0.235)   \npho_order           0.005           0.001           0.005** \n                  (0.003)         (0.004)         (0.002)   \nfemale              0.040           0.011          -0.026   \n                  (0.053)         (0.047)         (0.040)   \nage                -0.001          -0.002           0.000   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.023          -0.039           0.055   \n                  (0.154)         (0.122)         (0.085)   \nuniversity         -0.077           0.054           0.007   \n                  (0.054)         (0.068)         (0.040)   \n_cons               0.071          -0.004          -0.136   \n                  (0.135)         (0.160)         (0.088)   \n------------------------------------------------------------\nr2_w                0.016           0.013           0.059   \nr2_b                0.169           0.044           0.110   \nr2_o                0.032           0.016           0.068   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_3059\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_3059\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.220           0.121           0.221           0.223   \n                  (0.140)         (0.156)         (0.171)         (0.139)   \nwp_right2           0.140          -0.016           0.078           0.303   \n                  (0.119)         (0.082)         (0.086)         (0.185)   \nc.neg#c.wp~2       -0.261          -0.073          -0.307          -0.312   \n                  (0.351)         (0.240)         (0.266)         (0.388)   \npho_order           0.005           0.003           0.002           0.003   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale             -0.001           0.016           0.015           0.054   \n                  (0.037)         (0.027)         (0.033)         (0.063)   \nage                 0.001          -0.001          -0.002           0.006   \n                  (0.002)         (0.001)         (0.002)         (0.008)   \nincome             -0.087          -0.017          -0.013           0.083   \n                  (0.091)         (0.054)         (0.072)         (0.126)   \nuniversity          0.047          -0.012           0.008          -0.026   \n                  (0.037)         (0.029)         (0.038)         (0.088)   \n_cons              -0.184           0.015          -0.023          -0.301   \n                  (0.098)         (0.074)         (0.091)         (0.260)   \n----------------------------------------------------------------------------\nr2_w                0.016           0.009           0.006           0.019   \nr2_b                0.181           0.043           0.039           0.175   \nr2_o                0.025           0.012           0.007           0.036   \nN                 561.000         660.000         527.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.251           0.140           0.386   \n                  (0.207)         (0.088)         (0.265)   \nwp_right2          -0.078          -0.028          -0.078   \n                  (0.166)         (0.096)         (0.269)   \nc.neg#c.wp~2        0.742          -0.198          -0.286   \n                  (0.509)         (0.310)         (0.687)   \npho_order           0.011**         0.005**        -0.008   \n                  (0.004)         (0.002)         (0.005)   \nfemale             -0.110          -0.058          -0.064   \n                  (0.064)         (0.030)         (0.083)   \nage                 0.030          -0.004          -0.007   \n                  (0.016)         (0.003)         (0.027)   \nincome              0.045           0.072           0.204   \n                  (0.154)         (0.084)         (0.160)   \nuniversity          0.134           0.006          -0.185   \n                  (0.173)         (0.045)         (0.129)   \n_cons              -0.761*          0.043           0.382   \n                  (0.363)         (0.111)         (0.618)   \n------------------------------------------------------------\nr2_w                0.021           0.028           0.025   \nr2_b                0.285           0.178           0.165   \nr2_o                0.052           0.039           0.041   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_3059\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.271*          0.042          -0.141   \n                  (0.123)         (0.174)         (0.105)   \nwp_right2           0.008           0.151          -0.028   \n                  (0.121)         (0.090)         (0.055)   \nc.neg#c.wp~2       -0.518           0.124           0.304   \n                  (0.325)         (0.287)         (0.169)   \npho_order           0.002          -0.002           0.001   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.016          -0.042           0.020   \n                  (0.049)         (0.037)         (0.019)   \nage                 0.001          -0.002           0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.071          -0.058          -0.045   \n                  (0.077)         (0.095)         (0.057)   \nuniversity          0.012          -0.086           0.003   \n                  (0.047)         (0.057)         (0.019)   \n_cons              -0.077           0.084           0.013   \n                  (0.095)         (0.110)         (0.054)   \n------------------------------------------------------------\nr2_w                0.015           0.013           0.011   \nr2_b                0.088           0.248           0.068   \nr2_o                0.022           0.030           0.014   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.094           0.201          -0.072   \n                  (0.093)         (0.131)         (0.108)   \nwp_right2          -0.115           0.056           0.058   \n                  (0.118)         (0.119)         (0.085)   \nc.neg#c.wp~2        0.005          -0.634           0.353   \n                  (0.235)         (0.372)         (0.274)   \npho_order           0.002           0.003           0.002   \n                  (0.002)         (0.003)         (0.002)   \nfemale             -0.008           0.046           0.010   \n                  (0.053)         (0.042)         (0.028)   \nage                 0.004          -0.002          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.062          -0.119           0.098   \n                  (0.137)         (0.085)         (0.059)   \nuniversity          0.006          -0.055           0.035   \n                  (0.055)         (0.058)         (0.029)   \n_cons              -0.250*          0.074          -0.128   \n                  (0.116)         (0.092)         (0.069)   \n------------------------------------------------------------\nr2_w                0.012           0.007           0.003   \nr2_b                0.180           0.148           0.042   \nr2_o                0.042           0.019           0.006   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.          \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_7380\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_7380\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.041           0.410*          0.024   \n                  (0.032)         (0.169)         (0.124)   \nwp_right2           0.026          -0.065           0.083   \n                  (0.021)         (0.131)         (0.149)   \nc.neg#c.wp~2       -0.066          -0.962*         -0.044   \n                  (0.070)         (0.412)         (0.374)   \npho_order           0.004***        0.009**         0.007*  \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.000           0.004           0.111   \n                  (0.009)         (0.048)         (0.074)   \nage                -0.000          -0.004           0.000   \n                  (0.000)         (0.005)         (0.003)   \nincome             -0.015          -0.056          -0.070   \n                  (0.019)         (0.104)         (0.143)   \nuniversity          0.008           0.037           0.157*  \n                  (0.009)         (0.048)         (0.077)   \n_cons              -0.064**        -0.047          -0.273   \n                  (0.022)         (0.140)         (0.158)   \n------------------------------------------------------------\nr2_w                0.004           0.043           0.015   \nr2_b                0.008           0.156           0.253   \nr2_o                0.004           0.050           0.049   \nN                8835.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.077          -0.028           0.063   \n                  (0.149)         (0.236)         (0.073)   \nwp_right2          -0.268           0.008           0.017   \n                  (0.152)         (0.157)         (0.125)   \nc.neg#c.wp~2        0.218           0.210          -0.178   \n                  (0.402)         (0.461)         (0.215)   \npho_order           0.004           0.001           0.004*  \n                  (0.003)         (0.003)         (0.002)   \nfemale              0.047           0.002          -0.044   \n                  (0.054)         (0.042)         (0.043)   \nage                -0.001          -0.002           0.001   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.023           0.049          -0.019   \n                  (0.156)         (0.110)         (0.091)   \nuniversity         -0.088           0.019           0.009   \n                  (0.055)         (0.061)         (0.042)   \n_cons               0.063          -0.032          -0.095   \n                  (0.138)         (0.144)         (0.093)   \n------------------------------------------------------------\nr2_w                0.008           0.003           0.017   \nr2_b                0.141           0.023           0.081   \nr2_o                0.022           0.005           0.031   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_7380\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_7380\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.184           0.108          -0.163           0.017   \n                  (0.139)         (0.152)         (0.170)         (0.135)   \nwp_right2           0.099          -0.023           0.072           0.340   \n                  (0.118)         (0.085)         (0.086)         (0.200)   \nc.neg#c.wp~2       -0.381          -0.116           0.166          -0.095   \n                  (0.349)         (0.234)         (0.263)         (0.379)   \npho_order           0.008***        0.004*          0.002           0.004   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale              0.002           0.016           0.022           0.023   \n                  (0.037)         (0.029)         (0.033)         (0.068)   \nage                 0.002          -0.002          -0.002           0.010   \n                  (0.002)         (0.001)         (0.002)         (0.009)   \nincome             -0.129          -0.004          -0.024           0.048   \n                  (0.090)         (0.056)         (0.072)         (0.138)   \nuniversity          0.056           0.002           0.006          -0.060   \n                  (0.037)         (0.030)         (0.038)         (0.096)   \n_cons              -0.229*          0.001          -0.022          -0.360   \n                  (0.097)         (0.076)         (0.091)         (0.282)   \n----------------------------------------------------------------------------\nr2_w                0.024           0.010           0.006           0.006   \nr2_b                0.214           0.040           0.068           0.182   \nr2_o                0.037           0.013           0.010           0.029   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.079          -0.100           0.221   \n                  (0.211)         (0.087)         (0.249)   \nwp_right2          -0.114          -0.024          -0.146   \n                  (0.161)         (0.095)         (0.221)   \nc.neg#c.wp~2        0.392           0.316          -0.118   \n                  (0.520)         (0.307)         (0.645)   \npho_order           0.011**         0.006**        -0.003   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.113          -0.054          -0.096   \n                  (0.062)         (0.030)         (0.067)   \nage                 0.022          -0.004          -0.019   \n                  (0.016)         (0.002)         (0.022)   \nincome             -0.108           0.078           0.171   \n                  (0.148)         (0.083)         (0.131)   \nuniversity          0.100           0.023          -0.093   \n                  (0.167)         (0.045)         (0.105)   \n_cons              -0.502          -0.008           0.542   \n                  (0.351)         (0.110)         (0.508)   \n------------------------------------------------------------\nr2_w                0.017           0.028           0.009   \nr2_b                0.308           0.199           0.201   \nr2_o                0.048           0.038           0.026   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_7380\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.145           0.016           0.097   \n                  (0.116)         (0.160)         (0.101)   \nwp_right2           0.007           0.146          -0.036   \n                  (0.114)         (0.083)         (0.053)   \nc.neg#c.wp~2       -0.331          -0.079          -0.138   \n                  (0.305)         (0.262)         (0.162)   \npho_order           0.003           0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.015          -0.049           0.024   \n                  (0.046)         (0.034)         (0.018)   \nage                 0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.032          -0.021          -0.048   \n                  (0.072)         (0.087)         (0.055)   \nuniversity          0.016          -0.089          -0.009   \n                  (0.044)         (0.053)         (0.018)   \n_cons              -0.135           0.037           0.034   \n                  (0.090)         (0.100)         (0.052)   \n------------------------------------------------------------\nr2_w                0.006           0.001           0.003   \nr2_b                0.110           0.307           0.178   \nr2_o                0.015           0.024           0.010   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.027           0.010           0.075   \n                  (0.098)         (0.134)         (0.108)   \nwp_right2          -0.109           0.024           0.060   \n                  (0.108)         (0.122)         (0.086)   \nc.neg#c.wp~2        0.238          -0.322          -0.255   \n                  (0.248)         (0.381)         (0.274)   \npho_order           0.002           0.004           0.003   \n                  (0.002)         (0.003)         (0.002)   \nfemale             -0.005           0.031           0.013   \n                  (0.049)         (0.043)         (0.028)   \nage                 0.004          -0.001          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.082          -0.094           0.077   \n                  (0.124)         (0.087)         (0.059)   \nuniversity         -0.008          -0.011           0.034   \n                  (0.050)         (0.059)         (0.030)   \n_cons              -0.243*          0.002          -0.131   \n                  (0.107)         (0.095)         (0.069)   \n------------------------------------------------------------\nr2_w                0.006           0.007           0.002   \nr2_b                0.194           0.090           0.028   \nr2_o                0.033           0.012           0.004   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.          \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_9300\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_9300\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.006          -0.005          -0.025   \n                  (0.032)         (0.171)         (0.128)   \nwp_right2           0.026          -0.056           0.076   \n                  (0.022)         (0.127)         (0.141)   \nc.neg#c.wp~2       -0.054          -0.011          -0.183   \n                  (0.070)         (0.430)         (0.387)   \npho_order           0.004***        0.011***        0.008*  \n                  (0.001)         (0.003)         (0.003)   \nfemale             -0.002           0.001           0.097   \n                  (0.009)         (0.047)         (0.070)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.005)         (0.002)   \nincome              0.000          -0.026          -0.066   \n                  (0.020)         (0.101)         (0.135)   \nuniversity          0.005          -0.010           0.161*  \n                  (0.010)         (0.047)         (0.072)   \n_cons              -0.074***       -0.159          -0.301*  \n                  (0.022)         (0.137)         (0.151)   \n------------------------------------------------------------\nr2_w                0.005           0.039           0.023   \nr2_b                0.009           0.045           0.263   \nr2_o                0.005           0.040           0.052   \nN                8834.000         360.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.166          -0.096           0.085   \n                  (0.149)         (0.230)         (0.080)   \nwp_right2          -0.262           0.091          -0.033   \n                  (0.173)         (0.163)         (0.128)   \nc.neg#c.wp~2        0.390           0.025          -0.415   \n                  (0.404)         (0.450)         (0.236)   \npho_order           0.006*          0.003           0.006***\n                  (0.003)         (0.003)         (0.002)   \nfemale              0.069          -0.028          -0.061   \n                  (0.062)         (0.044)         (0.044)   \nage                -0.000          -0.002           0.001   \n                  (0.003)         (0.004)         (0.001)   \nincome              0.021          -0.049           0.080   \n                  (0.178)         (0.115)         (0.093)   \nuniversity         -0.067          -0.003          -0.004   \n                  (0.063)         (0.064)         (0.043)   \n_cons              -0.002          -0.019          -0.151   \n                  (0.154)         (0.150)         (0.096)   \n------------------------------------------------------------\nr2_w                0.015           0.005           0.046   \nr2_b                0.110           0.017           0.130   \nr2_o                0.027           0.006           0.063   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_9300\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_9300\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.120          -0.011           0.213           0.057   \n                  (0.141)         (0.153)         (0.168)         (0.132)   \nwp_right2           0.155          -0.022           0.073           0.334   \n                  (0.119)         (0.086)         (0.085)         (0.208)   \nc.neg#c.wp~2       -0.189           0.065          -0.490          -0.478   \n                  (0.353)         (0.235)         (0.260)         (0.369)   \npho_order           0.008**         0.003           0.002           0.003   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale             -0.022           0.023           0.008           0.040   \n                  (0.038)         (0.029)         (0.033)         (0.071)   \nage                 0.002          -0.001          -0.001           0.009   \n                  (0.002)         (0.001)         (0.002)         (0.009)   \nincome             -0.012          -0.011          -0.028           0.055   \n                  (0.091)         (0.057)         (0.071)         (0.143)   \nuniversity          0.043          -0.002           0.005          -0.039   \n                  (0.038)         (0.030)         (0.038)         (0.100)   \n_cons              -0.276**         0.006          -0.031          -0.355   \n                  (0.098)         (0.077)         (0.090)         (0.294)   \n----------------------------------------------------------------------------\nr2_w                0.017           0.006           0.015           0.016   \nr2_b                0.192           0.039           0.011           0.137   \nr2_o                0.027           0.009           0.015           0.033   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.143           0.084           0.388   \n                  (0.204)         (0.087)         (0.253)   \nwp_right2          -0.090          -0.027          -0.131   \n                  (0.166)         (0.094)         (0.225)   \nc.neg#c.wp~2        0.266          -0.610*         -0.729   \n                  (0.502)         (0.306)         (0.654)   \npho_order           0.012**         0.006**        -0.005   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.108          -0.058*         -0.049   \n                  (0.064)         (0.030)         (0.068)   \nage                 0.027          -0.005          -0.018   \n                  (0.016)         (0.002)         (0.022)   \nincome             -0.006           0.063           0.135   \n                  (0.154)         (0.082)         (0.132)   \nuniversity          0.102           0.017           0.016   \n                  (0.173)         (0.045)         (0.106)   \n_cons              -0.667           0.033           0.447   \n                  (0.362)         (0.110)         (0.513)   \n------------------------------------------------------------\nr2_w                0.023           0.046           0.013   \nr2_b                0.270           0.165           0.101   \nr2_o                0.052           0.054           0.017   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_9300\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.119           0.061          -0.128   \n                  (0.114)         (0.167)         (0.101)   \nwp_right2          -0.001           0.155          -0.032   \n                  (0.132)         (0.086)         (0.053)   \nc.neg#c.wp~2        0.208          -0.064           0.185   \n                  (0.302)         (0.274)         (0.162)   \npho_order           0.002           0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.017          -0.065           0.015   \n                  (0.053)         (0.036)         (0.018)   \nage                 0.002          -0.002          -0.001   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.040          -0.022          -0.044   \n                  (0.084)         (0.091)         (0.055)   \nuniversity          0.035          -0.079          -0.007   \n                  (0.051)         (0.055)         (0.018)   \n_cons              -0.145           0.033           0.039   \n                  (0.102)         (0.104)         (0.052)   \n------------------------------------------------------------\nr2_w                0.004           0.001           0.005   \nr2_b                0.117           0.296           0.125   \nr2_o                0.019           0.026           0.009   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.039          -0.166           0.049   \n                  (0.092)         (0.129)         (0.107)   \nwp_right2          -0.121           0.032           0.046   \n                  (0.117)         (0.117)         (0.087)   \nc.neg#c.wp~2       -0.057           0.165          -0.272   \n                  (0.235)         (0.365)         (0.272)   \npho_order           0.002           0.003           0.002   \n                  (0.002)         (0.003)         (0.002)   \nfemale              0.002           0.045          -0.010   \n                  (0.053)         (0.042)         (0.029)   \nage                 0.004*         -0.001          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nincome              0.107          -0.092           0.107   \n                  (0.136)         (0.083)         (0.060)   \nuniversity         -0.038          -0.045           0.033   \n                  (0.054)         (0.057)         (0.030)   \n_cons              -0.276*          0.026          -0.126   \n                  (0.115)         (0.090)         (0.069)   \n------------------------------------------------------------\nr2_w                0.004           0.009           0.003   \nr2_b                0.222           0.083           0.032   \nr2_o                0.044           0.015           0.005   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.          \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negative\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & (stimulus==\"p_9325\" | p_negative==0) ,\n>  re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & (stimulus==\"p_9325\"\n>  | p_negative==0) , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.071*          0.276           0.023   \n                  (0.032)         (0.165)         (0.124)   \nwp_right2           0.024          -0.052           0.082   \n                  (0.021)         (0.127)         (0.134)   \nc.neg#c.wp~2       -0.062          -0.656          -0.181   \n                  (0.070)         (0.402)         (0.374)   \npho_order           0.003***        0.011***        0.007*  \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.003           0.000           0.113   \n                  (0.009)         (0.047)         (0.066)   \nage                -0.000          -0.001           0.001   \n                  (0.000)         (0.005)         (0.002)   \nincome             -0.013          -0.045          -0.086   \n                  (0.019)         (0.102)         (0.128)   \nuniversity          0.002          -0.005           0.147*  \n                  (0.009)         (0.047)         (0.068)   \n_cons              -0.066**        -0.124          -0.275   \n                  (0.022)         (0.137)         (0.141)   \n------------------------------------------------------------\nr2_w                0.004           0.047           0.017   \nr2_b                0.009           0.079           0.291   \nr2_o                0.005           0.049           0.050   \nN                8835.000         361.000         297.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.207          -0.037           0.146*  \n                  (0.161)         (0.224)         (0.072)   \nwp_right2          -0.206           0.017           0.023   \n                  (0.148)         (0.168)         (0.106)   \nc.neg#c.wp~2        0.933*          0.061          -0.287   \n                  (0.435)         (0.438)         (0.215)   \npho_order           0.003           0.002           0.004** \n                  (0.003)         (0.003)         (0.002)   \nfemale              0.026          -0.013          -0.027   \n                  (0.053)         (0.045)         (0.036)   \nage                -0.001          -0.000           0.000   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.080           0.053           0.062   \n                  (0.151)         (0.118)         (0.077)   \nuniversity         -0.046           0.039           0.016   \n                  (0.053)         (0.066)         (0.036)   \n_cons               0.046          -0.095          -0.147   \n                  (0.134)         (0.153)         (0.080)   \n------------------------------------------------------------\nr2_w                0.016           0.001           0.029   \nr2_b                0.094           0.023           0.079   \nr2_o                0.021           0.003           0.037   \nN                 396.000         605.000         385.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & (stimulus==\"p_9325\"\n>  | p_negative==0) , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & (stimulus==\"p_9325\"\n>  | p_negative==0) , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.220          -0.052          -0.075           0.144   \n                  (0.136)         (0.154)         (0.176)         (0.137)   \nwp_right2           0.115          -0.028           0.076           0.333   \n                  (0.115)         (0.090)         (0.089)         (0.189)   \nc.neg#c.wp~2       -0.320           0.089           0.213          -0.246   \n                  (0.339)         (0.236)         (0.272)         (0.383)   \npho_order           0.008**         0.003           0.002           0.004   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \nfemale             -0.011           0.028           0.040           0.024   \n                  (0.036)         (0.030)         (0.034)         (0.064)   \nage                 0.002          -0.000          -0.003           0.008   \n                  (0.002)         (0.001)         (0.002)         (0.008)   \nincome             -0.097          -0.017          -0.014           0.073   \n                  (0.088)         (0.059)         (0.075)         (0.130)   \nuniversity          0.061          -0.010           0.012          -0.028   \n                  (0.036)         (0.032)         (0.040)         (0.091)   \n_cons              -0.234*         -0.024          -0.004          -0.349   \n                  (0.095)         (0.080)         (0.094)         (0.267)   \n----------------------------------------------------------------------------\nr2_w                0.027           0.004           0.005           0.012   \nr2_b                0.247           0.035           0.115           0.159   \nr2_o                0.039           0.008           0.011           0.029   \nN                 561.000         660.000         528.000         264.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.192           0.041          -0.228   \n                  (0.213)         (0.088)         (0.235)   \nwp_right2          -0.100          -0.014          -0.152   \n                  (0.162)         (0.096)         (0.208)   \nc.neg#c.wp~2       -0.448           0.159           0.506   \n                  (0.524)         (0.310)         (0.607)   \npho_order           0.011**         0.006**        -0.004   \n                  (0.004)         (0.002)         (0.004)   \nfemale             -0.115          -0.049          -0.083   \n                  (0.062)         (0.030)         (0.063)   \nage                 0.032*         -0.003          -0.023   \n                  (0.016)         (0.003)         (0.021)   \nincome             -0.069           0.001           0.175   \n                  (0.150)         (0.084)         (0.123)   \nuniversity          0.040           0.003          -0.057   \n                  (0.168)         (0.045)         (0.099)   \n_cons              -0.653           0.043           0.601   \n                  (0.353)         (0.111)         (0.476)   \n------------------------------------------------------------\nr2_w                0.019           0.035           0.006   \nr2_b                0.336           0.076           0.208   \nr2_o                0.054           0.038           0.021   \nN                 341.000         407.000         396.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & (stimulus==\"p_9325\" |\n>  p_negative==0) , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.188           0.216          -0.130   \n                  (0.121)         (0.181)         (0.104)   \nwp_right2           0.036           0.162          -0.033   \n                  (0.119)         (0.094)         (0.054)   \nc.neg#c.wp~2       -0.243          -0.123           0.187   \n                  (0.319)         (0.298)         (0.166)   \npho_order           0.003           0.001          -0.000   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.036          -0.057           0.014   \n                  (0.048)         (0.039)         (0.019)   \nage                 0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.050          -0.070          -0.049   \n                  (0.075)         (0.098)         (0.056)   \nuniversity         -0.002          -0.071          -0.009   \n                  (0.046)         (0.059)         (0.018)   \n_cons              -0.114           0.045           0.055   \n                  (0.093)         (0.113)         (0.053)   \n------------------------------------------------------------\nr2_w                0.013           0.016           0.003   \nr2_b                0.112           0.315           0.067   \nr2_o                0.021           0.035           0.006   \nN                 352.000         352.000         528.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.164           0.210           0.157   \n                  (0.099)         (0.133)         (0.108)   \nwp_right2          -0.104           0.058           0.037   \n                  (0.116)         (0.131)         (0.086)   \nc.neg#c.wp~2        0.648*         -0.283          -0.352   \n                  (0.253)         (0.378)         (0.275)   \npho_order          -0.000           0.003           0.003   \n                  (0.002)         (0.003)         (0.002)   \nfemale              0.001           0.062           0.006   \n                  (0.053)         (0.047)         (0.029)   \nage                 0.004*         -0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \nincome             -0.011          -0.154           0.111   \n                  (0.135)         (0.094)         (0.059)   \nuniversity          0.029          -0.073           0.011   \n                  (0.054)         (0.064)         (0.030)   \n_cons              -0.201           0.063          -0.144*  \n                  (0.115)         (0.100)         (0.069)   \n------------------------------------------------------------\nr2_w                0.023           0.009           0.003   \nr2_b                0.178           0.141           0.031   \nr2_o                0.046           0.023           0.005   \nN                 339.000         523.000        1529.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.                  \n. * Table A6 Row 2\n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(56,936 real changes made, 17,708 to missing)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 , re \n.   estimates store A\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.017          -0.036          -0.112          -0.078   \n                  (0.022)         (0.139)         (0.101)         (0.061)   \nwp_right2           0.063          -0.275          -0.112          -0.268   \n                  (0.052)         (0.325)         (0.571)         (0.203)   \nc.neg#c.wp~2        0.045           0.140           0.731*          0.134   \n                  (0.048)         (0.338)         (0.341)         (0.188)   \nvid_order          -0.074***       -0.071*         -0.122***       -0.042*  \n                  (0.005)         (0.030)         (0.030)         (0.019)   \nfemale             -0.027          -0.083           0.188          -0.013   \n                  (0.023)         (0.122)         (0.249)         (0.101)   \nage                 0.001           0.013           0.025          -0.002   \n                  (0.001)         (0.012)         (0.025)         (0.003)   \nincome              0.016           0.021          -0.201           0.050   \n                  (0.049)         (0.281)         (0.443)         (0.197)   \nuniversity         -0.021          -0.016          -0.167          -0.061   \n                  (0.025)         (0.129)         (0.336)         (0.105)   \n_cons               0.215***        0.097          -0.176           0.326   \n                  (0.055)         (0.349)         (0.779)         (0.228)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.048           0.152           0.059   \nr2_b                0.037           0.121           0.085           0.077   \nr2_o                0.046           0.057           0.129           0.063   \nN                4665.000         175.000         160.000         135.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.104          -0.086          -0.082   \n                  (0.120)         (0.186)         (0.082)   \nwp_right2           0.445          -0.112           0.067   \n                  (0.481)         (0.383)         (0.252)   \nc.neg#c.wp~2       -0.110           0.224           0.342   \n                  (0.329)         (0.361)         (0.239)   \nvid_order          -0.108***       -0.111***       -0.041*  \n                  (0.029)         (0.023)         (0.019)   \nfemale              0.170           0.006          -0.008   \n                  (0.172)         (0.105)         (0.086)   \nage                 0.005          -0.011           0.001   \n                  (0.007)         (0.010)         (0.003)   \nincome              0.100           0.429           0.252   \n                  (0.497)         (0.257)         (0.184)   \nuniversity          0.229          -0.133          -0.009   \n                  (0.176)         (0.153)         (0.085)   \n_cons              -0.341           0.668          -0.044   \n                  (0.426)         (0.355)         (0.200)   \n------------------------------------------------------------\nr2_w                0.099           0.094           0.042   \nr2_b                0.129           0.130           0.163   \nr2_o                0.108           0.099           0.057   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.068           0.153           0.109   \n                  (0.125)         (0.097)         (0.110)   \nwp_right2          -0.090          -0.077          -0.236   \n                  (0.394)         (0.161)         (0.209)   \nc.neg#c.wp~2        0.077          -0.205          -0.176   \n                  (0.311)         (0.149)         (0.172)   \nvid_order          -0.119***       -0.067***       -0.087***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.106          -0.124*         -0.110   \n                  (0.128)         (0.055)         (0.084)   \nage                -0.003           0.001           0.002   \n                  (0.007)         (0.003)         (0.006)   \nincome              0.029           0.156           0.117   \n                  (0.310)         (0.108)         (0.176)   \nuniversity         -0.077          -0.033          -0.101   \n                  (0.129)         (0.057)         (0.098)   \n_cons               0.708*          0.243           0.363   \n                  (0.332)         (0.145)         (0.219)   \n------------------------------------------------------------\nr2_w                0.106           0.109           0.101   \nr2_b                0.055           0.202           0.185   \nr2_o                0.095           0.131           0.120   \nN                 255.000         300.000         250.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.071           0.006           0.040   \n                  (0.088)         (0.161)         (0.057)   \nwp_right2           0.241          -0.379           0.070   \n                  (0.406)         (0.391)         (0.251)   \nc.neg#c.wp~2        0.220           0.194          -0.049   \n                  (0.309)         (0.402)         (0.200)   \nvid_order          -0.133***       -0.048          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.100           0.112          -0.178*  \n                  (0.132)         (0.152)         (0.082)   \nage                -0.011           0.010           0.001   \n                  (0.023)         (0.039)         (0.007)   \nincome             -0.392          -0.043           0.451*  \n                  (0.300)         (0.377)         (0.228)   \nuniversity         -0.254          -0.100           0.167   \n                  (0.188)         (0.292)         (0.124)   \n_cons               1.094           0.098          -0.090   \n                  (0.684)         (0.867)         (0.304)   \n------------------------------------------------------------\nr2_w                0.075           0.016           0.101   \nr2_b                0.154           0.163           0.205   \nr2_o                0.095           0.035           0.129   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.063          -0.060           0.082          -0.097   \n                  (0.170)         (0.080)         (0.152)         (0.069)   \nwp_right2           0.139           0.236           0.283           0.017   \n                  (0.484)         (0.246)         (0.252)         (0.137)   \nc.neg#c.wp~2       -0.004           0.208          -0.067           0.160   \n                  (0.445)         (0.211)         (0.252)         (0.112)   \nvid_order          -0.099**        -0.087***       -0.062*         -0.020*  \n                  (0.034)         (0.021)         (0.026)         (0.009)   \nfemale              0.073          -0.090           0.110          -0.008   \n                  (0.150)         (0.102)         (0.104)         (0.048)   \nage                -0.046          -0.004           0.005           0.003   \n                  (0.049)         (0.002)         (0.005)         (0.002)   \nincome             -0.389           0.094          -0.058           0.210   \n                  (0.291)         (0.160)         (0.263)         (0.146)   \nuniversity         -0.055           0.012          -0.075           0.015   \n                  (0.233)         (0.098)         (0.159)         (0.048)   \n_cons               1.526           0.390*         -0.066          -0.091   \n                  (1.120)         (0.195)         (0.311)         (0.134)   \n----------------------------------------------------------------------------\nr2_w                0.052           0.108           0.042           0.023   \nr2_b                0.189           0.331           0.225           0.112   \nr2_o                0.075           0.144           0.073           0.044   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.101          -0.012           0.051   \n                  (0.068)         (0.082)         (0.056)   \nwp_right2           0.108           0.012           0.125   \n                  (0.184)         (0.302)         (0.157)   \nc.neg#c.wp~2        0.198           0.274           0.005   \n                  (0.173)         (0.235)         (0.132)   \nvid_order          -0.025          -0.077***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.094          -0.097          -0.033   \n                  (0.085)         (0.110)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.425          -0.094          -0.010   \n                  (0.217)         (0.220)         (0.120)   \nuniversity          0.051          -0.054           0.078   \n                  (0.087)         (0.149)         (0.062)   \n_cons               0.161           0.480*         -0.006   \n                  (0.195)         (0.225)         (0.141)   \n------------------------------------------------------------\nr2_w                0.028           0.086           0.020   \nr2_b                0.219           0.058           0.026   \nr2_o                0.068           0.078           0.022   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if stimtype==\"single video\" & local==0 , re \n.   estimates store A\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.034*          0.038           0.017          -0.036   \n                  (0.013)         (0.073)         (0.070)         (0.043)   \nwp_right2_~2        0.016           0.004          -0.884*         -0.078   \n                  (0.025)         (0.134)         (0.350)         (0.110)   \nc.neg#c.wp~2        0.002          -0.071           0.503*         -0.055   \n                  (0.023)         (0.134)         (0.221)         (0.104)   \nvid_order          -0.074***       -0.071*         -0.114***       -0.040*  \n                  (0.005)         (0.030)         (0.031)         (0.019)   \nfemale             -0.027          -0.090          -0.163           0.006   \n                  (0.023)         (0.123)         (0.248)         (0.099)   \nage                 0.001           0.014           0.012          -0.002   \n                  (0.001)         (0.011)         (0.021)         (0.004)   \nincome              0.015           0.010          -0.106           0.020   \n                  (0.049)         (0.285)         (0.369)         (0.202)   \nuniversity         -0.024          -0.032           0.032          -0.043   \n                  (0.024)         (0.128)         (0.280)         (0.106)   \n_cons               0.236***       -0.005           0.182           0.243   \n                  (0.052)         (0.327)         (0.640)         (0.223)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.050           0.142           0.061   \nr2_b                0.036           0.089           0.234           0.032   \nr2_o                0.045           0.055           0.174           0.054   \nN                4665.000         175.000         160.000         135.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.104          -0.018          -0.003   \n                  (0.069)         (0.086)         (0.046)   \nwp_right2_~2        0.038          -0.088          -0.042   \n                  (0.223)         (0.103)         (0.103)   \nc.neg#c.wp~2       -0.157           0.064           0.109   \n                  (0.158)         (0.104)         (0.102)   \nvid_order          -0.109***       -0.110***       -0.040*  \n                  (0.028)         (0.023)         (0.019)   \nfemale              0.196           0.014          -0.030   \n                  (0.174)         (0.100)         (0.082)   \nage                 0.005          -0.011           0.000   \n                  (0.007)         (0.010)         (0.003)   \nincome             -0.034           0.451           0.293   \n                  (0.479)         (0.257)         (0.185)   \nuniversity          0.191          -0.124          -0.008   \n                  (0.178)         (0.150)         (0.085)   \n_cons              -0.128           0.652          -0.030   \n                  (0.356)         (0.339)         (0.186)   \n------------------------------------------------------------\nr2_w                0.106           0.093           0.039   \nr2_b                0.101           0.146           0.132   \nr2_o                0.104           0.101           0.051   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.095           0.191*          0.056   \n                  (0.064)         (0.081)         (0.073)   \nwp_right2_~2        0.009          -0.112          -0.031   \n                  (0.190)         (0.092)         (0.100)   \nc.neg#c.wp~2        0.001          -0.186*         -0.073   \n                  (0.137)         (0.085)         (0.085)   \nvid_order          -0.120***       -0.067***       -0.088***\n                  (0.027)         (0.012)         (0.018)   \nfemale             -0.107          -0.116*         -0.123   \n                  (0.128)         (0.054)         (0.086)   \nage                -0.004           0.001           0.001   \n                  (0.007)         (0.003)         (0.006)   \nincome              0.044           0.162           0.164   \n                  (0.320)         (0.105)         (0.176)   \nuniversity         -0.078          -0.016          -0.070   \n                  (0.127)         (0.057)         (0.098)   \n_cons               0.685*          0.292*          0.243   \n                  (0.316)         (0.140)         (0.191)   \n------------------------------------------------------------\nr2_w                0.106           0.120           0.100   \nr2_b                0.055           0.242           0.155   \nr2_o                0.094           0.149           0.111   \nN                 255.000         300.000         250.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.029           0.060           0.024   \n                  (0.058)         (0.085)         (0.030)   \nwp_right2_~2       -0.192          -0.083          -0.166   \n                  (0.249)         (0.171)         (0.166)   \nc.neg#c.wp~2        0.105           0.062           0.056   \n                  (0.191)         (0.168)         (0.126)   \nvid_order          -0.133***       -0.050          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.147           0.090          -0.187*  \n                  (0.135)         (0.151)         (0.081)   \nage                -0.025           0.014           0.000   \n                  (0.024)         (0.040)         (0.007)   \nincome             -0.501           0.007           0.486*  \n                  (0.302)         (0.375)         (0.225)   \nuniversity         -0.263          -0.085           0.120   \n                  (0.187)         (0.296)         (0.128)   \n_cons               1.584*         -0.118          -0.003   \n                  (0.642)         (0.842)         (0.291)   \n------------------------------------------------------------\nr2_w                0.074           0.015           0.102   \nr2_b                0.152           0.143           0.226   \nr2_o                0.095           0.030           0.135   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u\n> niversity if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.046          -0.020           0.056          -0.066   \n                  (0.078)         (0.049)         (0.101)         (0.041)   \nwp_right2_~2       -0.042           0.152           0.187          -0.028   \n                  (0.197)         (0.109)         (0.125)         (0.054)   \nc.neg#c.wp~2        0.105           0.110          -0.017           0.085   \n                  (0.184)         (0.098)         (0.119)         (0.047)   \nvid_order          -0.099**        -0.086***       -0.064*         -0.020*  \n                  (0.034)         (0.021)         (0.026)         (0.010)   \nfemale              0.060          -0.077           0.094          -0.002   \n                  (0.144)         (0.098)         (0.105)         (0.046)   \nage                -0.051          -0.003           0.005           0.003   \n                  (0.047)         (0.002)         (0.005)         (0.002)   \nincome             -0.408           0.085          -0.112           0.230   \n                  (0.285)         (0.154)         (0.266)         (0.137)   \nuniversity         -0.041          -0.021          -0.038           0.007   \n                  (0.240)         (0.102)         (0.161)         (0.048)   \n_cons               1.698           0.429*         -0.024          -0.069   \n                  (0.998)         (0.174)         (0.296)         (0.125)   \n----------------------------------------------------------------------------\nr2_w                0.054           0.107           0.042           0.027   \nr2_b                0.189           0.372           0.261           0.123   \nr2_o                0.076           0.151           0.079           0.049   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.071           0.072           0.054   \n                  (0.047)         (0.047)         (0.029)   \nwp_right2_~2        0.031           0.046           0.097   \n                  (0.095)         (0.146)         (0.066)   \nc.neg#c.wp~2        0.130          -0.017          -0.006   \n                  (0.092)         (0.118)         (0.057)   \nvid_order          -0.025          -0.076***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.093          -0.090          -0.028   \n                  (0.086)         (0.111)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.399          -0.084          -0.015   \n                  (0.222)         (0.217)         (0.119)   \nuniversity          0.045          -0.064           0.078   \n                  (0.087)         (0.151)         (0.061)   \n_cons               0.154           0.468*          0.019   \n                  (0.196)         (0.226)         (0.132)   \n------------------------------------------------------------\nr2_w                0.031           0.078           0.020   \nr2_b                0.220           0.065           0.034   \nr2_o                0.071           0.074           0.024   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if stimtype==\"single video\" & local==0 , re \n.   estimates store A\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.028           0.010          -0.085          -0.131*  \n                  (0.015)         (0.092)         (0.089)         (0.058)   \nwp_right2_~x        0.037          -0.076           0.167          -0.100   \n                  (0.023)         (0.123)         (0.213)         (0.096)   \nc.neg#c.wp~x        0.012           0.009           0.291*          0.152   \n                  (0.022)         (0.123)         (0.130)         (0.078)   \nvid_order          -0.074***       -0.071*         -0.132***       -0.044*  \n                  (0.005)         (0.030)         (0.030)         (0.019)   \nfemale             -0.027          -0.091           0.181          -0.013   \n                  (0.023)         (0.122)         (0.244)         (0.111)   \nage                 0.001           0.013           0.035          -0.003   \n                  (0.001)         (0.012)         (0.026)         (0.004)   \nincome              0.008           0.027          -0.153           0.043   \n                  (0.049)         (0.282)         (0.451)         (0.204)   \nuniversity         -0.024          -0.011          -0.173          -0.078   \n                  (0.024)         (0.132)         (0.328)         (0.110)   \n_cons               0.228***        0.038          -0.462           0.353   \n                  (0.052)         (0.335)         (0.811)         (0.237)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.047           0.158           0.095   \nr2_b                0.038           0.111           0.101           0.021   \nr2_o                0.046           0.055           0.138           0.076   \nN                4665.000         175.000         160.000         135.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.109          -0.004          -0.045   \n                  (0.088)         (0.064)         (0.058)   \nwp_right2_~x        0.145          -0.027           0.053   \n                  (0.174)         (0.112)         (0.089)   \nc.neg#c.wp~x       -0.073           0.069           0.127   \n                  (0.124)         (0.098)         (0.081)   \nvid_order          -0.109***       -0.111***       -0.043*  \n                  (0.028)         (0.023)         (0.019)   \nfemale              0.183           0.006           0.014   \n                  (0.170)         (0.109)         (0.089)   \nage                 0.005          -0.011           0.001   \n                  (0.007)         (0.010)         (0.003)   \nincome              0.104           0.437           0.240   \n                  (0.502)         (0.261)         (0.184)   \nuniversity          0.187          -0.136          -0.013   \n                  (0.171)         (0.151)         (0.085)   \n_cons              -0.232           0.628          -0.048   \n                  (0.376)         (0.339)         (0.194)   \n------------------------------------------------------------\nr2_w                0.102           0.095           0.043   \nr2_b                0.120           0.129           0.198   \nr2_o                0.107           0.100           0.063   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.117           0.086           0.023   \n                  (0.082)         (0.044)         (0.053)   \nwp_right2_~x        0.012          -0.002          -0.116   \n                  (0.133)         (0.059)         (0.084)   \nc.neg#c.wp~x       -0.041          -0.091          -0.040   \n                  (0.114)         (0.055)         (0.075)   \nvid_order          -0.120***       -0.067***       -0.089***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.106          -0.130*         -0.137   \n                  (0.127)         (0.055)         (0.083)   \nage                -0.004           0.001           0.002   \n                  (0.006)         (0.003)         (0.006)   \nincome              0.038           0.148           0.146   \n                  (0.302)         (0.107)         (0.170)   \nuniversity         -0.075          -0.037          -0.097   \n                  (0.131)         (0.057)         (0.095)   \n_cons               0.682*          0.205           0.275   \n                  (0.317)         (0.124)         (0.183)   \n------------------------------------------------------------\nr2_w                0.106           0.114           0.098   \nr2_b                0.058           0.190           0.194   \nr2_o                0.095           0.131           0.118   \nN                 255.000         300.000         250.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.020           0.094           0.043   \n                  (0.078)         (0.099)         (0.040)   \nwp_right2_~x        0.120          -0.146           0.042   \n                  (0.137)         (0.153)         (0.075)   \nc.neg#c.wp~x        0.000          -0.044          -0.032   \n                  (0.112)         (0.147)         (0.059)   \nvid_order          -0.132***       -0.051          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.125           0.066          -0.177*  \n                  (0.129)         (0.153)         (0.082)   \nage                -0.012           0.007           0.002   \n                  (0.022)         (0.040)         (0.007)   \nincome             -0.417          -0.001           0.447*  \n                  (0.294)         (0.371)         (0.226)   \nuniversity         -0.248          -0.098           0.168   \n                  (0.187)         (0.292)         (0.123)   \n_cons               1.122           0.096          -0.103   \n                  (0.616)         (0.875)         (0.304)   \n------------------------------------------------------------\nr2_w                0.075           0.015           0.103   \nr2_b                0.149           0.167           0.209   \nr2_o                0.094           0.035           0.131   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u\n> niversity if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.038          -0.002           0.034          -0.015   \n                  (0.095)         (0.061)         (0.070)         (0.027)   \nwp_right2_~x        0.068           0.045           0.149           0.032   \n                  (0.157)         (0.088)         (0.110)         (0.047)   \nc.neg#c.wp~x        0.052           0.013           0.017           0.029   \n                  (0.143)         (0.086)         (0.109)         (0.041)   \nvid_order          -0.099**        -0.087***       -0.061*         -0.019*  \n                  (0.034)         (0.021)         (0.026)         (0.009)   \nfemale              0.087          -0.137           0.113          -0.011   \n                  (0.152)         (0.091)         (0.103)         (0.048)   \nage                -0.042          -0.004           0.005           0.003   \n                  (0.047)         (0.002)         (0.005)         (0.002)   \nincome             -0.372           0.047          -0.082           0.191   \n                  (0.291)         (0.155)         (0.264)         (0.144)   \nuniversity         -0.050           0.028          -0.035           0.014   \n                  (0.232)         (0.096)         (0.162)         (0.047)   \n_cons               1.444           0.469**        -0.009          -0.093   \n                  (1.048)         (0.177)         (0.294)         (0.121)   \n----------------------------------------------------------------------------\nr2_w                0.053           0.102           0.041           0.017   \nr2_b                0.194           0.300           0.259           0.113   \nr2_o                0.077           0.134           0.078           0.041   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.053           0.086           0.039   \n                  (0.060)         (0.064)         (0.035)   \nwp_right2_~x        0.046           0.040           0.067   \n                  (0.086)         (0.115)         (0.059)   \nc.neg#c.wp~x        0.026          -0.034           0.028   \n                  (0.081)         (0.087)         (0.050)   \nvid_order          -0.025          -0.076***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.085          -0.093          -0.036   \n                  (0.085)         (0.109)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.449*         -0.089          -0.020   \n                  (0.222)         (0.220)         (0.121)   \nuniversity          0.067          -0.057           0.079   \n                  (0.090)         (0.148)         (0.062)   \n_cons               0.170           0.466*          0.016   \n                  (0.195)         (0.223)         (0.133)   \n------------------------------------------------------------\nr2_w                0.018           0.078           0.021   \nr2_b                0.215           0.070           0.030   \nr2_o                0.059           0.075           0.023   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.    \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if stimtype==\"single video\" & local==0 , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.006           0.024          -0.109          -0.049   \n                  (0.023)         (0.126)         (0.137)         (0.066)   \nleft_right2        -0.028          -0.226          -0.629          -0.330*  \n                  (0.045)         (0.251)         (0.576)         (0.167)   \nc.neg#c.le~2        0.058          -0.021           0.516          -0.005   \n                  (0.042)         (0.242)         (0.379)         (0.153)   \nvid_order          -0.074***       -0.072*         -0.117***       -0.041*  \n                  (0.005)         (0.030)         (0.031)         (0.019)   \nfemale             -0.029          -0.080           0.148          -0.002   \n                  (0.023)         (0.122)         (0.236)         (0.097)   \nage                 0.001           0.011           0.018          -0.004   \n                  (0.001)         (0.012)         (0.025)         (0.003)   \nincome              0.013           0.075          -0.107           0.080   \n                  (0.049)         (0.290)         (0.439)         (0.196)   \nuniversity         -0.026          -0.008          -0.164          -0.076   \n                  (0.024)         (0.130)         (0.317)         (0.105)   \n_cons               0.257***        0.136           0.122           0.421   \n                  (0.056)         (0.362)         (0.800)         (0.236)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.047           0.135           0.058   \nr2_b                0.034           0.127           0.105           0.149   \nr2_o                0.046           0.058           0.124           0.081   \nN                4660.000         175.000         160.000         135.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.031          -0.189          -0.021   \n                  (0.119)         (0.182)         (0.097)   \nleft_right2        -0.244          -0.541*          0.203   \n                  (0.400)         (0.256)         (0.202)   \nc.neg#c.le~2        0.291           0.319           0.085   \n                  (0.276)         (0.259)         (0.188)   \nvid_order          -0.105***       -0.109***       -0.043*  \n                  (0.029)         (0.022)         (0.019)   \nfemale              0.221           0.033           0.004   \n                  (0.181)         (0.098)         (0.083)   \nage                 0.005          -0.011           0.001   \n                  (0.007)         (0.010)         (0.003)   \nincome             -0.107           0.337           0.187   \n                  (0.471)         (0.252)         (0.199)   \nuniversity          0.192          -0.090          -0.002   \n                  (0.168)         (0.152)         (0.085)   \n_cons              -0.040           0.978**        -0.095   \n                  (0.379)         (0.373)         (0.201)   \n------------------------------------------------------------\nr2_w                0.103           0.099           0.036   \nr2_b                0.126           0.213           0.166   \nr2_o                0.109           0.116           0.052   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.065          -0.066           0.065   \n                  (0.134)         (0.078)         (0.085)   \nleft_right2         0.107           0.023          -0.086   \n                  (0.271)         (0.127)         (0.140)   \nc.neg#c.le~2        0.058           0.142          -0.109   \n                  (0.237)         (0.112)         (0.133)   \nvid_order          -0.119***       -0.068***       -0.089***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.113          -0.125*         -0.115   \n                  (0.129)         (0.055)         (0.079)   \nage                -0.004           0.001           0.001   \n                  (0.006)         (0.003)         (0.005)   \nincome              0.053           0.144           0.153   \n                  (0.305)         (0.109)         (0.167)   \nuniversity         -0.076          -0.029          -0.062   \n                  (0.128)         (0.061)         (0.086)   \n_cons               0.631           0.200           0.292   \n                  (0.345)         (0.137)         (0.203)   \n------------------------------------------------------------\nr2_w                0.106           0.113           0.095   \nr2_b                0.059           0.191           0.189   \nr2_o                0.095           0.131           0.113   \nN                 255.000         295.000         250.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.085           0.099           0.069   \n                  (0.130)         (0.275)         (0.061)   \nleft_right2        -0.309           0.274           0.198   \n                  (0.257)         (0.330)         (0.163)   \nc.neg#c.le~2        0.125          -0.034          -0.101   \n                  (0.218)         (0.342)         (0.131)   \nvid_order          -0.132***       -0.050          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.134           0.123          -0.166*  \n                  (0.131)         (0.155)         (0.081)   \nage                -0.016           0.011           0.001   \n                  (0.021)         (0.039)         (0.007)   \nincome             -0.420           0.020           0.423   \n                  (0.297)         (0.371)         (0.224)   \nuniversity         -0.222          -0.120           0.185   \n                  (0.192)         (0.292)         (0.122)   \n_cons               1.437*         -0.285          -0.164   \n                  (0.565)         (0.828)         (0.293)   \n------------------------------------------------------------\nr2_w                0.076           0.015           0.104   \nr2_b                0.154           0.153           0.238   \nr2_o                0.097           0.032           0.140   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer\n> sity if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.013          -0.154           0.169          -0.041   \n                  (0.229)         (0.091)         (0.171)         (0.033)   \nleft_right2         0.227           0.112           0.343           0.029   \n                  (0.465)         (0.235)         (0.377)         (0.065)   \nc.neg#c.le~2        0.107           0.393*         -0.261           0.083   \n                  (0.474)         (0.199)         (0.346)         (0.056)   \nvid_order          -0.101**        -0.086***       -0.066*         -0.021*  \n                  (0.034)         (0.021)         (0.026)         (0.010)   \nfemale              0.056          -0.108           0.095          -0.007   \n                  (0.142)         (0.103)         (0.110)         (0.047)   \nage                -0.047          -0.003           0.005           0.002   \n                  (0.045)         (0.002)         (0.006)         (0.002)   \nincome             -0.404           0.020          -0.008           0.184   \n                  (0.283)         (0.151)         (0.268)         (0.141)   \nuniversity         -0.040           0.036          -0.073           0.004   \n                  (0.229)         (0.092)         (0.160)         (0.045)   \n_cons               1.497           0.440*         -0.061          -0.057   \n                  (1.018)         (0.193)         (0.317)         (0.119)   \n----------------------------------------------------------------------------\nr2_w                0.052           0.127           0.048           0.023   \nr2_b                0.197           0.307           0.191           0.119   \nr2_o                0.076           0.157           0.072           0.046   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.150           0.111           0.044   \n                  (0.086)         (0.109)         (0.049)   \nleft_right2         0.132           0.318           0.048   \n                  (0.183)         (0.305)         (0.123)   \nc.neg#c.le~2        0.242          -0.107           0.020   \n                  (0.166)         (0.248)         (0.103)   \nvid_order          -0.027          -0.076***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.086          -0.080          -0.035   \n                  (0.083)         (0.109)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.494*         -0.120          -0.002   \n                  (0.231)         (0.215)         (0.120)   \nuniversity          0.050          -0.055           0.078   \n                  (0.086)         (0.147)         (0.062)   \n_cons               0.178           0.344           0.014   \n                  (0.192)         (0.251)         (0.141)   \n------------------------------------------------------------\nr2_w                0.032           0.078           0.020   \nr2_b                0.236           0.087           0.024   \nr2_o                0.075           0.080           0.021   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if stimtype==\"single video\" & local==0 , re \n.   estimates store A\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.020           0.021           0.063          -0.086   \n                  (0.016)         (0.095)         (0.095)         (0.061)   \nleft_right~x       -0.021          -0.102          -0.089          -0.163*  \n                  (0.023)         (0.121)         (0.212)         (0.082)   \nc.neg#c.le~x        0.028          -0.008          -0.018           0.071   \n                  (0.022)         (0.123)         (0.131)         (0.080)   \nvid_order          -0.074***       -0.072*         -0.121***       -0.042*  \n                  (0.005)         (0.030)         (0.031)         (0.019)   \nfemale             -0.029          -0.076           0.143           0.034   \n                  (0.023)         (0.123)         (0.246)         (0.092)   \nage                 0.001           0.013           0.019          -0.003   \n                  (0.001)         (0.012)         (0.027)         (0.003)   \nincome              0.014           0.015          -0.157           0.076   \n                  (0.049)         (0.279)         (0.450)         (0.188)   \nuniversity         -0.026          -0.022          -0.147          -0.070   \n                  (0.024)         (0.128)         (0.330)         (0.100)   \n_cons               0.253***        0.084          -0.023           0.361   \n                  (0.052)         (0.344)         (0.843)         (0.220)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.048           0.128           0.066   \nr2_b                0.035           0.120           0.060           0.117   \nr2_o                0.046           0.057           0.103           0.079   \nN                4660.000         175.000         160.000         135.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.020          -0.014           0.004   \n                  (0.088)         (0.064)         (0.057)   \nleft_right~x       -0.152          -0.178          -0.007   \n                  (0.187)         (0.096)         (0.089)   \nc.neg#c.le~x        0.192           0.090           0.032   \n                  (0.124)         (0.097)         (0.083)   \nvid_order          -0.107***       -0.109***       -0.042*  \n                  (0.028)         (0.022)         (0.020)   \nfemale              0.234           0.052          -0.023   \n                  (0.187)         (0.101)         (0.084)   \nage                 0.006          -0.011           0.000   \n                  (0.007)         (0.010)         (0.003)   \nincome             -0.165           0.434           0.279   \n                  (0.487)         (0.250)         (0.193)   \nuniversity          0.175          -0.139          -0.010   \n                  (0.170)         (0.149)         (0.087)   \n_cons              -0.041           0.667*         -0.024   \n                  (0.357)         (0.337)         (0.190)   \n------------------------------------------------------------\nr2_w                0.112           0.095           0.036   \nr2_b                0.124           0.196           0.105   \nr2_o                0.116           0.111           0.045   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.103          -0.005           0.024   \n                  (0.080)         (0.037)         (0.052)   \nleft_right~x       -0.013           0.041          -0.094   \n                  (0.130)         (0.058)         (0.077)   \nc.neg#c.le~x       -0.015           0.064          -0.044   \n                  (0.113)         (0.052)         (0.076)   \nvid_order          -0.120***       -0.068***       -0.090***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.105          -0.120*         -0.111   \n                  (0.128)         (0.056)         (0.079)   \nage                -0.004           0.001           0.001   \n                  (0.006)         (0.003)         (0.005)   \nincome              0.032           0.129           0.147   \n                  (0.305)         (0.109)         (0.163)   \nuniversity         -0.077          -0.026          -0.061   \n                  (0.127)         (0.058)         (0.087)   \n_cons               0.695*          0.201           0.283   \n                  (0.326)         (0.123)         (0.178)   \n------------------------------------------------------------\nr2_w                0.105           0.112           0.095   \nr2_b                0.057           0.202           0.202   \nr2_o                0.095           0.133           0.116   \nN                 255.000         295.000         250.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.043           0.130           0.040   \n                  (0.077)         (0.097)         (0.043)   \nleft_right~x       -0.235           0.039           0.053   \n                  (0.131)         (0.145)         (0.075)   \nc.neg#c.le~x        0.054          -0.125          -0.024   \n                  (0.111)         (0.148)         (0.059)   \nvid_order          -0.132***       -0.049          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.127           0.099          -0.173*  \n                  (0.129)         (0.153)         (0.081)   \nage                -0.014           0.017           0.002   \n                  (0.021)         (0.038)         (0.007)   \nincome             -0.395           0.014           0.440   \n                  (0.293)         (0.372)         (0.225)   \nuniversity         -0.196          -0.134           0.188   \n                  (0.189)         (0.292)         (0.128)   \n_cons               1.293*         -0.164          -0.131   \n                  (0.552)         (0.827)         (0.301)   \n------------------------------------------------------------\nr2_w                0.076           0.019           0.103   \nr2_b                0.175           0.145           0.210   \nr2_o                0.103           0.033           0.131   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income\n>  university if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004          -0.096           0.180          -0.049   \n                  (0.108)         (0.066)         (0.103)         (0.032)   \nleft_right~x        0.140          -0.022           0.207           0.047   \n                  (0.146)         (0.098)         (0.125)         (0.046)   \nc.neg#c.le~x        0.100           0.170*         -0.185           0.075   \n                  (0.142)         (0.086)         (0.120)         (0.041)   \nvid_order          -0.103**        -0.088***       -0.069**        -0.020*  \n                  (0.034)         (0.021)         (0.026)         (0.009)   \nfemale              0.021          -0.143           0.077          -0.010   \n                  (0.147)         (0.098)         (0.109)         (0.047)   \nage                -0.044          -0.003           0.004           0.002   \n                  (0.044)         (0.002)         (0.005)         (0.002)   \nincome             -0.401           0.031           0.014           0.165   \n                  (0.282)         (0.151)         (0.265)         (0.142)   \nuniversity         -0.063           0.036          -0.083           0.005   \n                  (0.228)         (0.093)         (0.158)         (0.046)   \n_cons               1.497           0.497**        -0.017          -0.071   \n                  (0.940)         (0.188)         (0.290)         (0.119)   \n----------------------------------------------------------------------------\nr2_w                0.058           0.132           0.064           0.032   \nr2_b                0.211           0.264           0.222           0.130   \nr2_o                0.083           0.154           0.091           0.057   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.104           0.076           0.050   \n                  (0.058)         (0.059)         (0.037)   \nleft_right~x        0.002           0.217*          0.007   \n                  (0.085)         (0.106)         (0.060)   \nc.neg#c.le~x        0.126          -0.016           0.004   \n                  (0.081)         (0.087)         (0.051)   \nvid_order          -0.027          -0.075***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.090          -0.054          -0.036   \n                  (0.085)         (0.107)         (0.062)   \nage                 0.003          -0.000           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.431          -0.169           0.003   \n                  (0.229)         (0.210)         (0.120)   \nuniversity          0.053          -0.018           0.076   \n                  (0.088)         (0.144)         (0.062)   \n_cons               0.182           0.344           0.030   \n                  (0.195)         (0.224)         (0.137)   \n------------------------------------------------------------\nr2_w                0.038           0.078           0.020   \nr2_b                0.199           0.151           0.023   \nr2_o                0.072           0.098           0.021   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if stimtype==\"single video\" & local==0 , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.001          -0.155          -0.064   \n                  (0.026)         (0.143)         (0.125)         (0.066)   \nideo_right2         0.015          -0.308          -0.427          -0.328   \n                  (0.058)         (0.318)         (0.613)         (0.189)   \nc.neg#c.id~2        0.075           0.032           0.773*          0.055   \n                  (0.053)         (0.314)         (0.392)         (0.176)   \nvid_order          -0.074***       -0.071*         -0.118***       -0.041*  \n                  (0.005)         (0.030)         (0.030)         (0.019)   \nfemale             -0.028          -0.079           0.158          -0.013   \n                  (0.023)         (0.122)         (0.240)         (0.098)   \nage                 0.001           0.011           0.022          -0.003   \n                  (0.001)         (0.012)         (0.025)         (0.003)   \nincome              0.013           0.065          -0.181           0.064   \n                  (0.049)         (0.287)         (0.434)         (0.196)   \nuniversity         -0.024          -0.008          -0.136          -0.066   \n                  (0.025)         (0.130)         (0.318)         (0.104)   \n_cons               0.235***        0.146          -0.033           0.377   \n                  (0.058)         (0.363)         (0.790)         (0.232)   \n----------------------------------------------------------------------------\nr2_w                0.050           0.047           0.146           0.058   \nr2_b                0.035           0.132           0.096           0.115   \nr2_o                0.046           0.058           0.128           0.072   \nN                4660.000         175.000         160.000         135.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014          -0.304          -0.062   \n                  (0.135)         (0.243)         (0.095)   \nideo_right2         0.052          -0.828           0.176   \n                  (0.525)         (0.427)         (0.241)   \nc.neg#c.id~2        0.174           0.565           0.213   \n                  (0.353)         (0.405)         (0.225)   \nvid_order          -0.107***       -0.110***       -0.042*  \n                  (0.029)         (0.022)         (0.019)   \nfemale              0.178           0.059           0.003   \n                  (0.180)         (0.102)         (0.085)   \nage                 0.005          -0.010           0.001   \n                  (0.007)         (0.010)         (0.003)   \nincome             -0.041           0.400           0.210   \n                  (0.491)         (0.250)         (0.193)   \nuniversity          0.196          -0.072          -0.003   \n                  (0.173)         (0.155)         (0.085)   \n_cons              -0.151           1.021**        -0.075   \n                  (0.422)         (0.389)         (0.203)   \n------------------------------------------------------------\nr2_w                0.099           0.101           0.037   \nr2_b                0.111           0.190           0.171   \nr2_o                0.103           0.115           0.054   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.063           0.017           0.135   \n                  (0.139)         (0.147)         (0.120)   \nideo_right2         0.052           0.001          -0.280   \n                  (0.344)         (0.252)         (0.233)   \nc.neg#c.id~2        0.074           0.016          -0.224   \n                  (0.291)         (0.224)         (0.195)   \nvid_order          -0.119***       -0.067***       -0.088***\n                  (0.026)         (0.012)         (0.018)   \nfemale             -0.109          -0.133*         -0.103   \n                  (0.129)         (0.055)         (0.080)   \nage                -0.004           0.001           0.001   \n                  (0.006)         (0.003)         (0.005)   \nincome              0.050           0.153           0.093   \n                  (0.307)         (0.112)         (0.174)   \nuniversity         -0.081          -0.039          -0.089   \n                  (0.128)         (0.059)         (0.090)   \n_cons               0.666           0.210           0.412   \n                  (0.343)         (0.178)         (0.234)   \n------------------------------------------------------------\nr2_w                0.106           0.103           0.098   \nr2_b                0.055           0.203           0.211   \nr2_o                0.095           0.126           0.121   \nN                 255.000         295.000         250.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.200          -0.119           0.060   \n                  (0.172)         (0.542)         (0.063)   \nideo_right2        -0.477          -0.019           0.186   \n                  (0.512)         (0.972)         (0.210)   \nc.neg#c.id~2        0.479           0.346          -0.098   \n                  (0.431)         (0.950)         (0.168)   \nvid_order          -0.134***       -0.052          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.138           0.090          -0.171*  \n                  (0.133)         (0.155)         (0.081)   \nage                -0.020           0.020           0.002   \n                  (0.022)         (0.039)         (0.007)   \nincome             -0.467           0.030           0.432   \n                  (0.294)         (0.379)         (0.226)   \nuniversity         -0.262          -0.104           0.179   \n                  (0.188)         (0.294)         (0.123)   \n_cons               1.600*         -0.214          -0.146   \n                  (0.646)         (0.969)         (0.299)   \n------------------------------------------------------------\nr2_w                0.077           0.017           0.103   \nr2_b                0.154           0.120           0.221   \nr2_o                0.097           0.029           0.135   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer\n> sity if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.039          -0.123           0.175          -0.089   \n                  (0.234)         (0.091)         (0.199)         (0.053)   \nideo_right2         0.264           0.197           0.547           0.049   \n                  (0.575)         (0.262)         (0.401)         (0.109)   \nc.neg#c.id~2        0.054           0.356          -0.246           0.165   \n                  (0.553)         (0.223)         (0.370)         (0.092)   \nvid_order          -0.100**        -0.086***       -0.061*         -0.021*  \n                  (0.034)         (0.021)         (0.026)         (0.010)   \nfemale              0.071          -0.090           0.083          -0.010   \n                  (0.144)         (0.105)         (0.108)         (0.047)   \nage                -0.043          -0.004           0.004           0.002   \n                  (0.048)         (0.002)         (0.006)         (0.002)   \nincome             -0.388           0.053          -0.026           0.181   \n                  (0.286)         (0.152)         (0.263)         (0.143)   \nuniversity         -0.053           0.027          -0.068           0.009   \n                  (0.230)         (0.094)         (0.159)         (0.045)   \n_cons               1.407           0.403*         -0.162          -0.068   \n                  (1.119)         (0.198)         (0.330)         (0.119)   \n----------------------------------------------------------------------------\nr2_w                0.052           0.119           0.046           0.028   \nr2_b                0.194           0.322           0.231           0.125   \nr2_o                0.076           0.152           0.077           0.051   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.139           0.027           0.045   \n                  (0.082)         (0.104)         (0.055)   \nideo_right2         0.135           0.186           0.090   \n                  (0.196)         (0.337)         (0.147)   \nc.neg#c.id~2        0.258           0.117           0.017   \n                  (0.183)         (0.270)         (0.123)   \nvid_order          -0.027          -0.076***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.092          -0.090          -0.034   \n                  (0.083)         (0.109)         (0.062)   \nage                 0.002          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.460*         -0.112          -0.006   \n                  (0.221)         (0.219)         (0.120)   \nuniversity          0.049          -0.057           0.079   \n                  (0.086)         (0.148)         (0.062)   \n_cons               0.168           0.427           0.001   \n                  (0.193)         (0.236)         (0.142)   \n------------------------------------------------------------\nr2_w                0.032           0.079           0.020   \nr2_b                0.229           0.071           0.025   \nr2_o                0.074           0.077           0.022   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if stimtype==\"single video\" & local==0 , re \n.   estimates store A  \n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"BR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"CA.e\" & stimtype==\"single video\" & local==0 , re \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"CA.f\" & stimtype==\"single video\" & local==0 , re \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"CH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"CN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"DK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.007           0.050          -0.037          -0.075   \n                  (0.015)         (0.088)         (0.095)         (0.056)   \nideo_right~x       -0.020          -0.177           0.066          -0.135   \n                  (0.023)         (0.124)         (0.210)         (0.083)   \nc.neg#c.id~x        0.056**        -0.069           0.171           0.058   \n                  (0.022)         (0.121)         (0.130)         (0.079)   \nvid_order          -0.074***       -0.074*         -0.121***       -0.042*  \n                  (0.005)         (0.029)         (0.030)         (0.019)   \nfemale             -0.029          -0.055           0.169           0.013   \n                  (0.023)         (0.123)         (0.244)         (0.096)   \nage                 0.001           0.010           0.029          -0.002   \n                  (0.001)         (0.012)         (0.026)         (0.003)   \nincome              0.012           0.000          -0.172           0.050   \n                  (0.049)         (0.277)         (0.453)         (0.194)   \nuniversity         -0.026           0.027          -0.154          -0.041   \n                  (0.024)         (0.132)         (0.329)         (0.103)   \n_cons               0.253***        0.144          -0.320           0.285   \n                  (0.052)         (0.341)         (0.796)         (0.218)   \n----------------------------------------------------------------------------\nr2_w                0.051           0.053           0.137           0.062   \nr2_b                0.035           0.165           0.071           0.093   \nr2_o                0.047           0.068           0.113           0.070   \nN                4660.000         175.000         160.000         135.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.024           0.007          -0.057   \n                  (0.088)         (0.063)         (0.057)   \nideo_right~x       -0.200          -0.269**         0.064   \n                  (0.185)         (0.099)         (0.085)   \nc.neg#c.id~x        0.194           0.058           0.153   \n                  (0.124)         (0.097)         (0.081)   \nvid_order          -0.106***       -0.111***       -0.041*  \n                  (0.028)         (0.022)         (0.019)   \nfemale              0.248           0.058           0.008   \n                  (0.180)         (0.099)         (0.083)   \nage                 0.007          -0.016           0.000   \n                  (0.007)         (0.010)         (0.003)   \nincome             -0.216           0.502*          0.215   \n                  (0.501)         (0.251)         (0.186)   \nuniversity          0.175          -0.103          -0.015   \n                  (0.170)         (0.148)         (0.084)   \n_cons              -0.044           0.791*         -0.023   \n                  (0.355)         (0.340)         (0.185)   \n------------------------------------------------------------\nr2_w                0.114           0.093           0.051   \nr2_b                0.132           0.279           0.213   \nr2_o                0.119           0.122           0.071   \nN                 180.000         280.000         175.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"FR\" & stimtype==\"single video\" & local==0 , re \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"GH\" & stimtype==\"single video\" & local==0 , re \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"IN\" & stimtype==\"single video\" & local==0 , re \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"IS.j\" & stimtype==\"single video\" & local==0 , re \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"IS.p\" & stimtype==\"single video\" & local==0 , re \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"IT\" & stimtype==\"single video\" & local==0 , re \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.122           0.028           0.032   \n                  (0.082)         (0.038)         (0.055)   \nideo_right~x       -0.005          -0.008          -0.113   \n                  (0.132)         (0.055)         (0.084)   \nc.neg#c.id~x       -0.051          -0.001          -0.053   \n                  (0.114)         (0.053)         (0.076)   \nvid_order          -0.120***       -0.067***       -0.089***\n                  (0.026)         (0.013)         (0.018)   \nfemale             -0.106          -0.134*         -0.114   \n                  (0.128)         (0.055)         (0.079)   \nage                -0.004           0.001           0.003   \n                  (0.006)         (0.003)         (0.006)   \nincome              0.028           0.155           0.097   \n                  (0.307)         (0.106)         (0.171)   \nuniversity         -0.071          -0.040          -0.085   \n                  (0.128)         (0.057)         (0.089)   \n_cons               0.692*          0.212           0.258   \n                  (0.324)         (0.122)         (0.176)   \n------------------------------------------------------------\nr2_w                0.106           0.103           0.096   \nr2_b                0.059           0.204           0.204   \nr2_o                0.095           0.126           0.118   \nN                 255.000         295.000         250.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.093           0.023           0.044   \n                  (0.079)         (0.107)         (0.042)   \nideo_right~x       -0.155          -0.048           0.051   \n                  (0.128)         (0.150)         (0.075)   \nc.neg#c.id~x        0.149           0.104          -0.033   \n                  (0.111)         (0.148)         (0.059)   \nvid_order          -0.133***       -0.054          -0.056***\n                  (0.026)         (0.035)         (0.014)   \nfemale             -0.140           0.080          -0.171*  \n                  (0.130)         (0.156)         (0.081)   \nage                -0.019           0.021           0.002   \n                  (0.021)         (0.039)         (0.007)   \nincome             -0.464           0.017           0.443*  \n                  (0.292)         (0.373)         (0.223)   \nuniversity         -0.261          -0.089           0.187   \n                  (0.186)         (0.292)         (0.129)   \n_cons               1.463**        -0.213          -0.131   \n                  (0.559)         (0.823)         (0.301)   \n------------------------------------------------------------\nr2_w                0.078           0.019           0.104   \nr2_b                0.165           0.122           0.207   \nr2_o                0.101           0.031           0.132   \nN                 355.000         160.000         185.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"JP\" & stimtype==\"single video\" & local==0 , re \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"NZ\" & stimtype==\"single video\" & local==0 , re \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"RU\" & stimtype==\"single video\" & local==0 , re \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"SE\" & stimtype==\"single video\" & local==0 , re \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"SW\" & stimtype==\"single video\" & local==0 , re \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"UK\" & stimtype==\"single video\" & local==0 , re \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income\n>  university if country2==\"US\" & stimtype==\"single video\" & local==0 , re \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.036          -0.108           0.043          -0.025   \n                  (0.102)         (0.060)         (0.073)         (0.028)   \nideo_right~x       -0.014           0.087           0.193           0.025   \n                  (0.146)         (0.101)         (0.110)         (0.047)   \nc.neg#c.id~x        0.057           0.225**         0.005           0.047   \n                  (0.142)         (0.083)         (0.106)         (0.040)   \nvid_order          -0.099**        -0.083***       -0.061*         -0.021*  \n                  (0.034)         (0.020)         (0.026)         (0.010)   \nfemale              0.057          -0.071           0.098          -0.011   \n                  (0.143)         (0.104)         (0.103)         (0.048)   \nage                -0.052          -0.003           0.004           0.002   \n                  (0.046)         (0.002)         (0.005)         (0.002)   \nincome             -0.402           0.049          -0.105           0.182   \n                  (0.285)         (0.148)         (0.263)         (0.144)   \nuniversity         -0.042           0.060          -0.036           0.007   \n                  (0.229)         (0.091)         (0.160)         (0.046)   \n_cons               1.711           0.376*          0.007          -0.059   \n                  (0.998)         (0.189)         (0.289)         (0.121)   \n----------------------------------------------------------------------------\nr2_w                0.053           0.146           0.041           0.021   \nr2_b                0.185           0.339           0.300           0.109   \nr2_o                0.076           0.178           0.085           0.043   \nN                 180.000         160.000         160.000         240.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.104           0.047           0.039   \n                  (0.058)         (0.062)         (0.035)   \nideo_right~x        0.002           0.149           0.044   \n                  (0.085)         (0.105)         (0.059)   \nc.neg#c.id~x        0.126           0.042           0.027   \n                  (0.081)         (0.087)         (0.050)   \nvid_order          -0.027          -0.077***       -0.042***\n                  (0.020)         (0.020)         (0.012)   \nfemale              0.090          -0.078          -0.036   \n                  (0.085)         (0.106)         (0.062)   \nage                 0.003          -0.001           0.002   \n                  (0.003)         (0.004)         (0.003)   \nincome             -0.431          -0.122          -0.013   \n                  (0.229)         (0.209)         (0.121)   \nuniversity          0.053          -0.034           0.080   \n                  (0.088)         (0.144)         (0.062)   \n_cons               0.182           0.420           0.019   \n                  (0.195)         (0.220)         (0.134)   \n------------------------------------------------------------\nr2_w                0.038           0.080           0.021   \nr2_b                0.199           0.110           0.025   \nr2_o                0.072           0.088           0.022   \nN                 155.000         240.000         920.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.   \n. * Table A6 Row 5\n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(56,936 real changes made, 39,228 to missing)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.007   \n                  (0.003)         (0.017)         (0.013)   \nwp_right2           0.050          -0.105           0.009   \n                  (0.037)         (0.214)         (0.220)   \nc.neg#c.wp~2       -0.012           0.011           0.015   \n                  (0.007)         (0.042)         (0.040)   \npho_order           0.002***        0.005*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.023           0.070   \n                  (0.007)         (0.037)         (0.061)   \nage                -0.000          -0.002           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.018          -0.087          -0.145   \n                  (0.015)         (0.079)         (0.118)   \nuniversity          0.006           0.015           0.121   \n                  (0.007)         (0.037)         (0.063)   \n_cons              -0.070**         0.008          -0.178   \n                  (0.023)         (0.131)         (0.142)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.014   \nr2_b                0.015           0.178           0.232   \nr2_o                0.003           0.018           0.032   \nN               15263.000         623.000         513.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003          -0.009           0.007   \n                  (0.016)         (0.027)         (0.009)   \nwp_right2          -0.288          -0.071          -0.026   \n                  (0.230)         (0.274)         (0.145)   \nc.neg#c.wp~2        0.037           0.030          -0.004   \n                  (0.044)         (0.052)         (0.026)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.031           0.039          -0.067*  \n                  (0.040)         (0.036)         (0.028)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome             -0.005           0.013           0.036   \n                  (0.115)         (0.095)         (0.060)   \nuniversity         -0.051           0.012          -0.013   \n                  (0.041)         (0.053)         (0.028)   \n_cons               0.073          -0.070          -0.060   \n                  (0.125)         (0.174)         (0.075)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.012   \nr2_b                0.155           0.056           0.192   \nr2_o                0.008           0.004           0.027   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.030*          0.014           0.005           0.012   \n                  (0.015)         (0.015)         (0.017)         (0.013)   \nwp_right2           0.212           0.020           0.061           0.322   \n                  (0.197)         (0.124)         (0.136)         (0.205)   \nc.neg#c.wp~2       -0.029          -0.015          -0.015          -0.041   \n                  (0.038)         (0.023)         (0.026)         (0.037)   \npho_order           0.005*          0.003*          0.001           0.001   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.018           0.020           0.026           0.004   \n                  (0.030)         (0.022)         (0.025)         (0.039)   \nage                 0.000          -0.000          -0.001           0.002   \n                  (0.002)         (0.001)         (0.002)         (0.005)   \nincome             -0.046          -0.025          -0.029          -0.029   \n                  (0.074)         (0.043)         (0.055)         (0.078)   \nuniversity          0.072*         -0.022           0.020           0.007   \n                  (0.030)         (0.023)         (0.029)         (0.055)   \n_cons              -0.283**        -0.045          -0.014          -0.143   \n                  (0.106)         (0.090)         (0.104)         (0.173)   \n----------------------------------------------------------------------------\nr2_w                0.016           0.006           0.002           0.003   \nr2_b                0.267           0.073           0.064           0.115   \nr2_o                0.024           0.011           0.004           0.008   \nN                 969.000        1140.000         911.000         456.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.037           0.008           0.027   \n                  (0.019)         (0.010)         (0.026)   \nwp_right2          -0.385           0.020           0.061   \n                  (0.247)         (0.178)         (0.359)   \nc.neg#c.wp~2        0.072          -0.012          -0.015   \n                  (0.048)         (0.035)         (0.068)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.032          -0.032           0.019   \n                  (0.044)         (0.026)         (0.054)   \nage                 0.005          -0.002           0.014   \n                  (0.011)         (0.002)         (0.018)   \nincome             -0.145           0.120           0.058   \n                  (0.106)         (0.072)         (0.105)   \nuniversity          0.133          -0.004          -0.105   \n                  (0.119)         (0.039)         (0.085)   \n_cons              -0.064          -0.048          -0.282   \n                  (0.266)         (0.107)         (0.423)   \n------------------------------------------------------------\nr2_w                0.017           0.011           0.007   \nr2_b                0.212           0.124           0.095   \nr2_o                0.030           0.017           0.010   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.046***        0.057**        -0.009   \n                  (0.013)         (0.019)         (0.011)   \nwp_right2           0.201           0.402*         -0.093   \n                  (0.191)         (0.164)         (0.088)   \nc.neg#c.wp~2       -0.077*         -0.072*          0.019   \n                  (0.035)         (0.032)         (0.017)   \npho_order           0.001          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.003          -0.014           0.016   \n                  (0.043)         (0.032)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.001          -0.061          -0.037   \n                  (0.068)         (0.080)         (0.043)   \nuniversity         -0.013          -0.036           0.001   \n                  (0.041)         (0.048)         (0.014)   \n_cons              -0.133          -0.170           0.056   \n                  (0.102)         (0.127)         (0.064)   \n------------------------------------------------------------\nr2_w                0.025           0.018           0.004   \nr2_b                0.163           0.136           0.108   \nr2_o                0.033           0.022           0.006   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009           0.009           0.016   \n                  (0.011)         (0.012)         (0.011)   \nwp_right2          -0.104           0.046           0.100   \n                  (0.152)         (0.178)         (0.142)   \nc.neg#c.wp~2        0.015          -0.018          -0.019   \n                  (0.029)         (0.034)         (0.028)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.059           0.053           0.005   \n                  (0.032)         (0.030)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.012          -0.078           0.045   \n                  (0.082)         (0.061)         (0.045)   \nuniversity          0.022          -0.053           0.021   \n                  (0.033)         (0.041)         (0.023)   \n_cons              -0.154           0.010          -0.090   \n                  (0.090)         (0.087)         (0.072)   \n------------------------------------------------------------\nr2_w                0.009           0.002           0.002   \nr2_b                0.193           0.152           0.033   \nr2_o                0.020           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011***        0.009           0.011   \n                  (0.002)         (0.009)         (0.009)   \nwp_right2_~2        0.039*         -0.019           0.075   \n                  (0.017)         (0.084)         (0.120)   \nc.neg#c.wp~2       -0.008*          0.002          -0.003   \n                  (0.003)         (0.016)         (0.022)   \npho_order           0.002***        0.005*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.025           0.066   \n                  (0.007)         (0.037)         (0.058)   \nage                -0.000          -0.002          -0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.017          -0.089          -0.125   \n                  (0.015)         (0.080)         (0.118)   \nuniversity          0.007           0.012           0.115   \n                  (0.007)         (0.036)         (0.062)   \n_cons              -0.065***       -0.021          -0.188   \n                  (0.018)         (0.113)         (0.131)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.014   \nr2_b                0.015           0.165           0.251   \nr2_o                0.004           0.017           0.034   \nN               15263.000         623.000         513.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010          -0.000           0.007   \n                  (0.010)         (0.013)         (0.005)   \nwp_right2_~2       -0.025           0.003           0.026   \n                  (0.112)         (0.079)         (0.061)   \nc.neg#c.wp~2       -0.004           0.009          -0.006   \n                  (0.022)         (0.015)         (0.011)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.031           0.037          -0.062*  \n                  (0.040)         (0.035)         (0.027)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome              0.019           0.000           0.031   \n                  (0.111)         (0.095)         (0.061)   \nuniversity         -0.050           0.012          -0.012   \n                  (0.041)         (0.052)         (0.028)   \n_cons              -0.030          -0.102          -0.073   \n                  (0.097)         (0.131)         (0.063)   \n------------------------------------------------------------\nr2_w                0.002           0.002           0.012   \nr2_b                0.137           0.085           0.185   \nr2_o                0.006           0.006           0.027   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.024**         0.005           0.000           0.001   \n                  (0.008)         (0.013)         (0.011)         (0.008)   \nwp_right2_~2        0.078          -0.004           0.022           0.093   \n                  (0.089)         (0.072)         (0.065)         (0.098)   \nc.neg#c.wp~2       -0.016          -0.000          -0.007          -0.006   \n                  (0.017)         (0.013)         (0.013)         (0.019)   \npho_order           0.005*          0.003*          0.001           0.001   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.019           0.019           0.025           0.016   \n                  (0.030)         (0.022)         (0.025)         (0.041)   \nage                 0.001          -0.000          -0.001           0.002   \n                  (0.002)         (0.001)         (0.002)         (0.005)   \nincome             -0.056          -0.028          -0.029          -0.035   \n                  (0.077)         (0.043)         (0.054)         (0.076)   \nuniversity          0.075*         -0.025           0.019           0.002   \n                  (0.030)         (0.023)         (0.029)         (0.055)   \n_cons              -0.233**        -0.023           0.006          -0.048   \n                  (0.084)         (0.081)         (0.077)         (0.136)   \n----------------------------------------------------------------------------\nr2_w                0.016           0.006           0.002           0.001   \nr2_b                0.244           0.063           0.066           0.136   \nr2_o                0.023           0.010           0.004           0.007   \nN                 969.000        1140.000         911.000         456.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.010           0.005           0.018   \n                  (0.010)         (0.005)         (0.013)   \nwp_right2_~2       -0.013          -0.053          -0.028   \n                  (0.105)         (0.115)         (0.147)   \nc.neg#c.wp~2       -0.001           0.000           0.016   \n                  (0.020)         (0.022)         (0.028)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.034          -0.035           0.025   \n                  (0.044)         (0.026)         (0.052)   \nage                 0.005          -0.002           0.019   \n                  (0.012)         (0.002)         (0.017)   \nincome             -0.140           0.125           0.068   \n                  (0.105)         (0.072)         (0.103)   \nuniversity          0.143          -0.014          -0.124   \n                  (0.121)         (0.040)         (0.087)   \n_cons              -0.209          -0.030          -0.342   \n                  (0.245)         (0.096)         (0.366)   \n------------------------------------------------------------\nr2_w                0.013           0.011           0.008   \nr2_b                0.209           0.146           0.116   \nr2_o                0.026           0.018           0.011   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in\n> come university if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.026**         0.041**        -0.003   \n                  (0.008)         (0.013)         (0.006)   \nwp_right2_~2        0.051           0.196*         -0.013   \n                  (0.089)         (0.081)         (0.037)   \nc.neg#c.wp~2       -0.019          -0.035*          0.006   \n                  (0.016)         (0.016)         (0.007)   \npho_order           0.001          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.020          -0.015           0.015   \n                  (0.043)         (0.032)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.022          -0.071          -0.042   \n                  (0.068)         (0.081)         (0.042)   \nuniversity         -0.018          -0.030           0.006   \n                  (0.045)         (0.049)         (0.014)   \n_cons              -0.092          -0.086           0.010   \n                  (0.085)         (0.107)         (0.048)   \n------------------------------------------------------------\nr2_w                0.019           0.018           0.003   \nr2_b                0.112           0.135           0.140   \nr2_o                0.024           0.022           0.006   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012           0.007           0.015** \n                  (0.008)         (0.007)         (0.005)   \nwp_right2_~2       -0.033           0.084           0.102   \n                  (0.079)         (0.088)         (0.059)   \nc.neg#c.wp~2        0.010          -0.020          -0.023   \n                  (0.015)         (0.017)         (0.012)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.065*          0.052           0.004   \n                  (0.033)         (0.031)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome             -0.007          -0.082           0.047   \n                  (0.084)         (0.060)         (0.045)   \nuniversity          0.020          -0.053           0.020   \n                  (0.033)         (0.042)         (0.022)   \n_cons              -0.173*          0.014          -0.078   \n                  (0.082)         (0.073)         (0.055)   \n------------------------------------------------------------\nr2_w                0.009           0.003           0.003   \nr2_b                0.189           0.148           0.033   \nr2_o                0.019           0.011           0.004   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.   \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.004          -0.000   \n                  (0.002)         (0.011)         (0.013)   \nwp_right2_~x        0.001          -0.080          -0.076   \n                  (0.016)         (0.078)         (0.097)   \nc.neg#c.wp~x       -0.002           0.010           0.019   \n                  (0.003)         (0.015)         (0.017)   \npho_order           0.002***        0.005*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.011          -0.026           0.065   \n                  (0.007)         (0.036)         (0.065)   \nage                -0.000          -0.003           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.017          -0.078          -0.144   \n                  (0.015)         (0.080)         (0.119)   \nuniversity          0.006           0.019           0.121   \n                  (0.007)         (0.037)         (0.064)   \n_cons              -0.051**         0.013          -0.134   \n                  (0.019)         (0.116)         (0.142)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.016   \nr2_b                0.016           0.214           0.219   \nr2_o                0.003           0.019           0.033   \nN               15263.000         623.000         513.000   \nN_g               804.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.007           0.004           0.008   \n                  (0.012)         (0.009)         (0.006)   \nwp_right2_~x       -0.051          -0.009           0.003   \n                  (0.089)         (0.077)         (0.050)   \nc.neg#c.wp~x        0.003           0.005          -0.004   \n                  (0.017)         (0.015)         (0.009)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.027           0.040          -0.068*  \n                  (0.040)         (0.038)         (0.029)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome             -0.004           0.013           0.037   \n                  (0.117)         (0.096)         (0.060)   \nuniversity         -0.040           0.015          -0.013   \n                  (0.040)         (0.052)         (0.028)   \n_cons              -0.003          -0.113          -0.066   \n                  (0.106)         (0.126)         (0.068)   \n------------------------------------------------------------\nr2_w                0.002           0.001           0.012   \nr2_b                0.139           0.053           0.193   \nr2_o                0.007           0.004           0.027   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.026**         0.012          -0.007           0.020   \n                  (0.010)         (0.007)         (0.008)         (0.012)   \nwp_right2_~x        0.059           0.036          -0.038           0.218** \n                  (0.071)         (0.045)         (0.056)         (0.082)   \nc.neg#c.wp~x       -0.011          -0.010           0.005          -0.034*  \n                  (0.014)         (0.008)         (0.011)         (0.015)   \npho_order           0.005*          0.003*          0.001           0.000   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.020           0.017           0.025          -0.012   \n                  (0.030)         (0.022)         (0.025)         (0.040)   \nage                 0.001          -0.000          -0.001           0.002   \n                  (0.002)         (0.001)         (0.002)         (0.004)   \nincome             -0.059          -0.028          -0.029          -0.034   \n                  (0.072)         (0.043)         (0.054)         (0.075)   \nuniversity          0.072*         -0.025           0.017           0.009   \n                  (0.031)         (0.023)         (0.029)         (0.054)   \n_cons              -0.244**        -0.053           0.041          -0.151   \n                  (0.089)         (0.057)         (0.067)         (0.144)   \n----------------------------------------------------------------------------\nr2_w                0.016           0.007           0.002           0.012   \nr2_b                0.247           0.067           0.072           0.149   \nr2_o                0.023           0.012           0.004           0.018   \nN                 969.000        1140.000         911.000         456.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.022           0.007           0.018   \n                  (0.012)         (0.007)         (0.015)   \nwp_right2_~x       -0.133           0.007          -0.056   \n                  (0.092)         (0.052)         (0.118)   \nc.neg#c.wp~x        0.023          -0.004           0.008   \n                  (0.018)         (0.010)         (0.023)   \npho_order           0.007*          0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.040          -0.032           0.013   \n                  (0.045)         (0.026)         (0.055)   \nage                 0.005          -0.002           0.013   \n                  (0.011)         (0.002)         (0.017)   \nincome             -0.140           0.118           0.051   \n                  (0.103)         (0.072)         (0.105)   \nuniversity          0.123          -0.004          -0.102   \n                  (0.120)         (0.039)         (0.084)   \n_cons              -0.116          -0.043          -0.197   \n                  (0.258)         (0.102)         (0.384)   \n------------------------------------------------------------\nr2_w                0.016           0.011           0.007   \nr2_b                0.213           0.125           0.099   \nr2_o                0.029           0.017           0.010   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in\n> come university if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.027**         0.032***       -0.003   \n                  (0.010)         (0.009)         (0.004)   \nwp_right2_~x       -0.014           0.148*         -0.064*  \n                  (0.074)         (0.072)         (0.031)   \nc.neg#c.wp~x       -0.010          -0.036*          0.011   \n                  (0.014)         (0.014)         (0.006)   \npho_order           0.002          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.016          -0.007           0.017   \n                  (0.038)         (0.031)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.013          -0.053          -0.031   \n                  (0.064)         (0.080)         (0.042)   \nuniversity         -0.016          -0.043           0.000   \n                  (0.040)         (0.049)         (0.014)   \n_cons              -0.078          -0.024           0.027   \n                  (0.088)         (0.097)         (0.041)   \n------------------------------------------------------------\nr2_w                0.018           0.020           0.006   \nr2_b                0.185           0.111           0.152   \nr2_o                0.027           0.024           0.009   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014           0.004           0.012   \n                  (0.010)         (0.009)         (0.006)   \nwp_right2_~x       -0.030          -0.011           0.030   \n                  (0.070)         (0.067)         (0.050)   \nc.neg#c.wp~x       -0.000          -0.000          -0.005   \n                  (0.013)         (0.013)         (0.010)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.060           0.053           0.005   \n                  (0.031)         (0.030)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome              0.001          -0.078           0.044   \n                  (0.083)         (0.061)         (0.045)   \nuniversity          0.014          -0.055           0.021   \n                  (0.033)         (0.041)         (0.022)   \n_cons              -0.177*          0.030          -0.066   \n                  (0.085)         (0.079)         (0.057)   \n------------------------------------------------------------\nr2_w                0.008           0.001           0.002   \nr2_b                0.214           0.151           0.034   \nr2_o                0.020           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.    \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012***        0.018           0.012   \n                  (0.003)         (0.015)         (0.015)   \nleft_right2         0.038           0.092          -0.003   \n                  (0.031)         (0.151)         (0.185)   \nc.neg#c.le~2       -0.008          -0.017          -0.004   \n                  (0.006)         (0.029)         (0.034)   \npho_order           0.002***        0.006*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.028           0.058   \n                  (0.007)         (0.036)         (0.059)   \nage                -0.000          -0.002           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.018          -0.098          -0.142   \n                  (0.015)         (0.082)         (0.119)   \nuniversity          0.007           0.011           0.119   \n                  (0.007)         (0.037)         (0.064)   \n_cons              -0.068**        -0.063          -0.173   \n                  (0.023)         (0.131)         (0.153)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.014   \nr2_b                0.015           0.164           0.218   \nr2_o                0.003           0.018           0.031   \nN               15244.000         623.000         513.000   \nN_g               803.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.003          -0.010           0.010   \n                  (0.016)         (0.032)         (0.010)   \nleft_right2        -0.095           0.087           0.040   \n                  (0.198)         (0.230)         (0.114)   \nc.neg#c.le~2        0.014           0.023          -0.009   \n                  (0.038)         (0.045)         (0.020)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.030           0.040          -0.061*  \n                  (0.043)         (0.034)         (0.027)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome              0.027           0.007           0.030   \n                  (0.112)         (0.094)         (0.065)   \nuniversity         -0.041          -0.004          -0.012   \n                  (0.040)         (0.053)         (0.028)   \n_cons              -0.003          -0.167          -0.086   \n                  (0.119)         (0.200)         (0.079)   \n------------------------------------------------------------\nr2_w                0.002           0.002           0.012   \nr2_b                0.104           0.121           0.184   \nr2_o                0.006           0.007           0.027   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.023           0.008          -0.002          -0.022   \n                  (0.016)         (0.012)         (0.013)         (0.017)   \nleft_right2         0.106          -0.026           0.020          -0.180   \n                  (0.148)         (0.094)         (0.102)         (0.140)   \nc.neg#c.le~2       -0.006          -0.004          -0.005           0.040   \n                  (0.029)         (0.017)         (0.020)         (0.027)   \npho_order           0.004*          0.003*          0.001           0.000   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.015           0.016           0.027           0.002   \n                  (0.031)         (0.023)         (0.025)         (0.042)   \nage                 0.001          -0.000          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.002)         (0.004)   \nincome             -0.051          -0.019          -0.028          -0.060   \n                  (0.073)         (0.044)         (0.055)         (0.078)   \nuniversity          0.078*         -0.034           0.021          -0.001   \n                  (0.030)         (0.025)         (0.027)         (0.057)   \n_cons              -0.268*         -0.016           0.014           0.159   \n                  (0.111)         (0.078)         (0.087)         (0.141)   \n----------------------------------------------------------------------------\nr2_w                0.015           0.006           0.002           0.006   \nr2_b                0.291           0.077           0.063           0.048   \nr2_o                0.024           0.011           0.004           0.007   \nN                 969.000        1121.000         911.000         456.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.033           0.013           0.001   \n                  (0.032)         (0.011)         (0.036)   \nleft_right2         0.247           0.067          -0.056   \n                  (0.206)         (0.117)         (0.380)   \nc.neg#c.le~2       -0.057          -0.018           0.044   \n                  (0.040)         (0.023)         (0.074)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.035          -0.032           0.018   \n                  (0.045)         (0.026)         (0.052)   \nage                 0.006          -0.002           0.018   \n                  (0.011)         (0.002)         (0.016)   \nincome             -0.133           0.118           0.060   \n                  (0.104)         (0.073)         (0.102)   \nuniversity          0.140          -0.004          -0.103   \n                  (0.120)         (0.040)         (0.083)   \n_cons              -0.427          -0.074          -0.311   \n                  (0.276)         (0.106)         (0.406)   \n------------------------------------------------------------\nr2_w                0.017           0.012           0.008   \nr2_b                0.207           0.121           0.130   \nr2_o                0.029           0.017           0.012   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income \n> university if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.029           0.030          -0.005   \n                  (0.015)         (0.020)         (0.005)   \nleft_right2         0.085           0.164          -0.050   \n                  (0.186)         (0.219)         (0.043)   \nc.neg#c.le~2       -0.017          -0.031           0.014   \n                  (0.033)         (0.042)         (0.008)   \npho_order           0.002          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.037          -0.011           0.015   \n                  (0.046)         (0.033)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.032          -0.054          -0.047   \n                  (0.067)         (0.082)         (0.043)   \nuniversity         -0.032          -0.037           0.002   \n                  (0.041)         (0.049)         (0.014)   \n_cons              -0.118          -0.029           0.032   \n                  (0.110)         (0.133)         (0.043)   \n------------------------------------------------------------\nr2_w                0.017           0.010           0.005   \nr2_b                0.093           0.101           0.130   \nr2_o                0.022           0.014           0.008   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.007           0.016           0.012   \n                  (0.014)         (0.016)         (0.009)   \nleft_right2        -0.147           0.111           0.009   \n                  (0.144)         (0.184)         (0.104)   \nc.neg#c.le~2        0.015          -0.029          -0.006   \n                  (0.028)         (0.036)         (0.020)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.062*          0.052           0.004   \n                  (0.031)         (0.031)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome              0.024          -0.081           0.049   \n                  (0.087)         (0.061)         (0.045)   \nuniversity          0.025          -0.054           0.019   \n                  (0.033)         (0.042)         (0.023)   \n_cons              -0.150          -0.014          -0.060   \n                  (0.096)         (0.104)         (0.066)   \n------------------------------------------------------------\nr2_w                0.009           0.002           0.002   \nr2_b                0.224           0.149           0.034   \nr2_o                0.021           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.    \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.006**         0.018           0.008   \n                  (0.002)         (0.012)         (0.013)   \nleft_right~x       -0.019           0.063          -0.063   \n                  (0.016)         (0.078)         (0.095)   \nc.neg#c.le~x        0.004          -0.014           0.004   \n                  (0.003)         (0.015)         (0.017)   \npho_order           0.002***        0.006*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.027           0.062   \n                  (0.007)         (0.036)         (0.058)   \nage                -0.000          -0.003          -0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.017          -0.094          -0.133   \n                  (0.015)         (0.079)         (0.118)   \nuniversity          0.006           0.012           0.114   \n                  (0.007)         (0.036)         (0.063)   \n_cons              -0.040*         -0.057          -0.135   \n                  (0.019)         (0.118)         (0.143)   \n------------------------------------------------------------\nr2_w                0.003           0.014           0.014   \nr2_b                0.015           0.162           0.245   \nr2_o                0.003           0.018           0.033   \nN               15244.000         623.000         513.000   \nN_g               803.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.006           0.001           0.010   \n                  (0.012)         (0.010)         (0.006)   \nleft_right~x       -0.030          -0.023           0.050   \n                  (0.090)         (0.074)         (0.050)   \nc.neg#c.le~x        0.004           0.011          -0.010   \n                  (0.017)         (0.014)         (0.009)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.029           0.038          -0.059*  \n                  (0.044)         (0.035)         (0.027)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome              0.026           0.017           0.026   \n                  (0.114)         (0.094)         (0.063)   \nuniversity         -0.041           0.016          -0.010   \n                  (0.040)         (0.051)         (0.029)   \n_cons              -0.024          -0.101          -0.090   \n                  (0.103)         (0.126)         (0.066)   \n------------------------------------------------------------\nr2_w                0.002           0.002           0.013   \nr2_b                0.102           0.065           0.186   \nr2_o                0.005           0.005           0.028   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.024*          0.004          -0.002          -0.009   \n                  (0.010)         (0.006)         (0.008)         (0.010)   \nleft_right~x        0.063          -0.053           0.007          -0.097   \n                  (0.070)         (0.044)         (0.055)         (0.080)   \nc.neg#c.le~x       -0.009           0.002          -0.005           0.021   \n                  (0.014)         (0.008)         (0.011)         (0.015)   \npho_order           0.005*          0.003*          0.001           0.001   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.017           0.009           0.028           0.001   \n                  (0.031)         (0.022)         (0.025)         (0.041)   \nage                 0.001          -0.000          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.002)         (0.004)   \nincome             -0.051          -0.010          -0.031          -0.059   \n                  (0.073)         (0.043)         (0.054)         (0.078)   \nuniversity          0.076*         -0.037           0.021           0.000   \n                  (0.030)         (0.023)         (0.027)         (0.059)   \n_cons              -0.250**        -0.007           0.021           0.098   \n                  (0.090)         (0.055)         (0.067)         (0.124)   \n----------------------------------------------------------------------------\nr2_w                0.015           0.006           0.002           0.005   \nr2_b                0.263           0.118           0.079           0.047   \nr2_o                0.023           0.014           0.004           0.007   \nN                 969.000        1121.000         911.000         456.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.008           0.005   \n                  (0.012)         (0.007)         (0.017)   \nleft_right~x        0.087           0.032          -0.090   \n                  (0.092)         (0.052)         (0.117)   \nc.neg#c.le~x       -0.020          -0.006           0.029   \n                  (0.018)         (0.010)         (0.023)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.033          -0.031           0.008   \n                  (0.044)         (0.026)         (0.053)   \nage                 0.006          -0.002           0.016   \n                  (0.011)         (0.002)         (0.016)   \nincome             -0.134           0.115           0.062   \n                  (0.104)         (0.073)         (0.102)   \nuniversity          0.138           0.000          -0.110   \n                  (0.120)         (0.041)         (0.083)   \n_cons              -0.267          -0.068          -0.245   \n                  (0.240)         (0.103)         (0.351)   \n------------------------------------------------------------\nr2_w                0.015           0.011           0.010   \nr2_b                0.207           0.119           0.127   \nr2_o                0.028           0.017           0.013   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age \n> income university if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.018           0.024          -0.008   \n                  (0.011)         (0.013)         (0.005)   \nleft_right~x       -0.042           0.042          -0.062*  \n                  (0.079)         (0.081)         (0.031)   \nc.neg#c.le~x        0.006          -0.011           0.016*  \n                  (0.014)         (0.016)         (0.006)   \npho_order           0.002          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.029          -0.007           0.016   \n                  (0.043)         (0.033)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.034          -0.060          -0.047   \n                  (0.067)         (0.082)         (0.043)   \nuniversity         -0.034          -0.038           0.002   \n                  (0.041)         (0.049)         (0.014)   \n_cons              -0.057           0.011           0.044   \n                  (0.097)         (0.107)         (0.042)   \n------------------------------------------------------------\nr2_w                0.017           0.010           0.010   \nr2_b                0.097           0.101           0.134   \nr2_o                0.022           0.013           0.012   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.008           0.007           0.006   \n                  (0.010)         (0.009)         (0.007)   \nleft_right~x       -0.112           0.005          -0.043   \n                  (0.069)         (0.066)         (0.050)   \nc.neg#c.le~x        0.012          -0.006           0.007   \n                  (0.013)         (0.013)         (0.010)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.059           0.049           0.002   \n                  (0.031)         (0.030)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome              0.030          -0.074           0.049   \n                  (0.085)         (0.060)         (0.045)   \nuniversity          0.018          -0.058           0.018   \n                  (0.033)         (0.041)         (0.023)   \n_cons              -0.157           0.032          -0.034   \n                  (0.084)         (0.078)         (0.059)   \n------------------------------------------------------------\nr2_w                0.010           0.002           0.002   \nr2_b                0.279           0.161           0.036   \nr2_o                0.026           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.     \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***        0.014           0.009   \n                  (0.004)         (0.017)         (0.015)   \nideo_right2         0.061           0.033           0.002   \n                  (0.040)         (0.198)         (0.211)   \nc.neg#c.id~2       -0.014          -0.010           0.004   \n                  (0.008)         (0.038)         (0.039)   \npho_order           0.002***        0.006*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.026           0.061   \n                  (0.007)         (0.036)         (0.060)   \nage                -0.000          -0.003           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.018          -0.091          -0.145   \n                  (0.015)         (0.081)         (0.119)   \nuniversity          0.007           0.013           0.121   \n                  (0.007)         (0.037)         (0.064)   \n_cons              -0.077**        -0.035          -0.180   \n                  (0.025)         (0.135)         (0.149)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.014   \nr2_b                0.014           0.163           0.218   \nr2_o                0.003           0.017           0.031   \nN               15244.000         623.000         513.000   \nN_g               803.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002          -0.020           0.009   \n                  (0.018)         (0.038)         (0.010)   \nideo_right2        -0.242           0.073           0.017   \n                  (0.247)         (0.330)         (0.137)   \nc.neg#c.id~2        0.032           0.044          -0.008   \n                  (0.047)         (0.063)         (0.024)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.035           0.027          -0.064*  \n                  (0.042)         (0.035)         (0.028)   \nage                -0.001           0.001          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome              0.009          -0.004           0.036   \n                  (0.114)         (0.094)         (0.063)   \nuniversity         -0.045          -0.010          -0.012   \n                  (0.040)         (0.054)         (0.028)   \n_cons               0.053          -0.124          -0.075   \n                  (0.130)         (0.223)         (0.079)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.012   \nr2_b                0.129           0.113           0.186   \nr2_o                0.007           0.007           0.027   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.028           0.022           0.006          -0.011   \n                  (0.017)         (0.022)         (0.019)         (0.020)   \nideo_right2         0.173          -0.035           0.069          -0.055   \n                  (0.182)         (0.185)         (0.163)         (0.229)   \nc.neg#c.id~2       -0.017          -0.026          -0.017           0.026   \n                  (0.035)         (0.034)         (0.031)         (0.044)   \npho_order           0.004*          0.003*          0.001           0.001   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.016           0.016           0.027           0.008   \n                  (0.031)         (0.022)         (0.025)         (0.042)   \nage                 0.001           0.000          -0.001          -0.000   \n                  (0.002)         (0.001)         (0.002)         (0.004)   \nincome             -0.047          -0.009          -0.029          -0.055   \n                  (0.073)         (0.044)         (0.056)         (0.077)   \nuniversity          0.075*         -0.037           0.021          -0.002   \n                  (0.030)         (0.024)         (0.028)         (0.057)   \n_cons              -0.284*         -0.024          -0.015           0.058   \n                  (0.113)         (0.125)         (0.117)         (0.168)   \n----------------------------------------------------------------------------\nr2_w                0.015           0.006           0.002           0.001   \nr2_b                0.285           0.106           0.064           0.065   \nr2_o                0.024           0.014           0.004           0.004   \nN                 969.000        1121.000         911.000         456.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.007           0.012           0.015   \n                  (0.064)         (0.011)         (0.036)   \nideo_right2        -0.095           0.063           0.024   \n                  (0.585)         (0.151)         (0.441)   \nc.neg#c.id~2       -0.031          -0.019           0.017   \n                  (0.113)         (0.029)         (0.085)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.039          -0.032           0.024   \n                  (0.045)         (0.026)         (0.052)   \nage                 0.006          -0.002           0.018   \n                  (0.011)         (0.002)         (0.017)   \nincome             -0.152           0.119           0.067   \n                  (0.106)         (0.073)         (0.104)   \nuniversity          0.152          -0.005          -0.110   \n                  (0.121)         (0.040)         (0.083)   \n_cons              -0.184          -0.066          -0.351   \n                  (0.402)         (0.108)         (0.439)   \n------------------------------------------------------------\nr2_w                0.013           0.011           0.007   \nr2_b                0.225           0.123           0.106   \nr2_o                0.027           0.017           0.010   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income \n> university if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.041**         0.064**        -0.012   \n                  (0.015)         (0.025)         (0.008)   \nideo_right2         0.164           0.529*         -0.098   \n                  (0.205)         (0.240)         (0.072)   \nc.neg#c.id~2       -0.054          -0.094*          0.025   \n                  (0.037)         (0.046)         (0.014)   \npho_order           0.001          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.017          -0.018           0.015   \n                  (0.046)         (0.033)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.027          -0.052          -0.047   \n                  (0.066)         (0.080)         (0.044)   \nuniversity         -0.027          -0.035           0.002   \n                  (0.041)         (0.049)         (0.014)   \n_cons              -0.138          -0.212           0.060   \n                  (0.110)         (0.148)         (0.052)   \n------------------------------------------------------------\nr2_w                0.020           0.016           0.006   \nr2_b                0.111           0.129           0.119   \nr2_o                0.026           0.021           0.008   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.007           0.014           0.014   \n                  (0.014)         (0.015)         (0.010)   \nideo_right2        -0.146           0.096           0.048   \n                  (0.160)         (0.201)         (0.129)   \nc.neg#c.id~2        0.017          -0.028          -0.012   \n                  (0.031)         (0.039)         (0.025)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.059           0.052           0.004   \n                  (0.032)         (0.031)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome              0.003          -0.079           0.047   \n                  (0.083)         (0.061)         (0.045)   \nuniversity          0.023          -0.054           0.019   \n                  (0.033)         (0.041)         (0.023)   \n_cons              -0.146          -0.007          -0.074   \n                  (0.095)         (0.099)         (0.070)   \n------------------------------------------------------------\nr2_w                0.009           0.002           0.002   \nr2_b                0.209           0.151           0.033   \nr2_o                0.021           0.010           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n.         \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"BR\" & stimtype==\"single photo\" , re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"CA.f\" & stimtype==\"single photo\" , re \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"CH\" & stimtype==\"single photo\" , re \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"CN\" & stimtype==\"single photo\" , re \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"DK\" & stimtype==\"single photo\" , re \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.014           0.009   \n                  (0.002)         (0.011)         (0.012)   \nideo_right~x        0.007           0.053          -0.061   \n                  (0.016)         (0.078)         (0.093)   \nc.neg#c.id~x       -0.001          -0.008           0.003   \n                  (0.003)         (0.015)         (0.017)   \npho_order           0.002***        0.006*          0.006*  \n                  (0.000)         (0.002)         (0.003)   \nfemale              0.012          -0.030           0.055   \n                  (0.007)         (0.037)         (0.058)   \nage                -0.000          -0.002           0.000   \n                  (0.000)         (0.004)         (0.002)   \nincome             -0.018          -0.093          -0.141   \n                  (0.015)         (0.078)         (0.116)   \nuniversity          0.007           0.007           0.124*  \n                  (0.007)         (0.038)         (0.062)   \n_cons              -0.054**        -0.048          -0.158   \n                  (0.019)         (0.117)         (0.137)   \n------------------------------------------------------------\nr2_w                0.003           0.013           0.014   \nr2_b                0.015           0.173           0.249   \nr2_o                0.003           0.018           0.033   \nN               15244.000         623.000         513.000   \nN_g               803.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.006          -0.000           0.011   \n                  (0.012)         (0.010)         (0.006)   \nideo_right~x       -0.019          -0.002           0.027   \n                  (0.090)         (0.075)         (0.050)   \nc.neg#c.id~x        0.004           0.013          -0.010   \n                  (0.017)         (0.014)         (0.009)   \npho_order           0.002           0.002           0.003*  \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.024           0.034          -0.068*  \n                  (0.042)         (0.035)         (0.027)   \nage                -0.001           0.002          -0.000   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.034          -0.011           0.042   \n                  (0.118)         (0.095)         (0.061)   \nuniversity         -0.041           0.010          -0.012   \n                  (0.040)         (0.052)         (0.028)   \n_cons              -0.028          -0.126          -0.085   \n                  (0.103)         (0.128)         (0.065)   \n------------------------------------------------------------\nr2_w                0.002           0.002           0.014   \nr2_b                0.100           0.108           0.201   \nr2_o                0.005           0.007           0.030   \nN                 684.000        1045.000         665.000   \nN_g                36.000          55.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"FR\" & stimtype==\"single photo\" , re \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"GH\" & stimtype==\"single photo\" , re \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"IN\" & stimtype==\"single photo\" , re \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"IS.j\" & stimtype==\"single photo\" , re \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"IS.p\" & stimtype==\"single photo\" , re \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"IT\" & stimtype==\"single photo\" , re \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"JP\" & stimtype==\"single photo\" , re \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.023*          0.009          -0.001          -0.005   \n                  (0.010)         (0.006)         (0.008)         (0.012)   \nideo_right~x        0.046          -0.004           0.039          -0.011   \n                  (0.071)         (0.044)         (0.056)         (0.081)   \nc.neg#c.id~x       -0.005          -0.007          -0.007           0.008   \n                  (0.014)         (0.008)         (0.011)         (0.015)   \npho_order           0.005*          0.003*          0.001           0.001   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nfemale              0.018           0.015           0.026           0.006   \n                  (0.031)         (0.022)         (0.025)         (0.041)   \nage                 0.001          -0.000          -0.001          -0.001   \n                  (0.002)         (0.001)         (0.002)         (0.004)   \nincome             -0.050          -0.022          -0.021          -0.062   \n                  (0.074)         (0.043)         (0.056)         (0.077)   \nuniversity          0.073*         -0.031           0.023           0.011   \n                  (0.030)         (0.023)         (0.028)         (0.060)   \n_cons              -0.240**        -0.032           0.007           0.039   \n                  (0.090)         (0.055)         (0.068)         (0.139)   \n----------------------------------------------------------------------------\nr2_w                0.015           0.007           0.002           0.001   \nr2_b                0.259           0.109           0.068           0.070   \nr2_o                0.023           0.014           0.004           0.004   \nN                 969.000        1121.000         911.000         456.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.001           0.009           0.016   \n                  (0.013)         (0.007)         (0.016)   \nideo_right~x        0.115           0.029          -0.024   \n                  (0.092)         (0.052)         (0.116)   \nc.neg#c.id~x       -0.023          -0.007           0.010   \n                  (0.018)         (0.010)         (0.023)   \npho_order           0.007**         0.004*         -0.003   \n                  (0.003)         (0.002)         (0.003)   \nfemale             -0.032          -0.032           0.022   \n                  (0.045)         (0.026)         (0.052)   \nage                 0.006          -0.002           0.017   \n                  (0.011)         (0.002)         (0.016)   \nincome             -0.132           0.117           0.064   \n                  (0.105)         (0.072)         (0.103)   \nuniversity          0.133          -0.004          -0.104   \n                  (0.121)         (0.042)         (0.083)   \n_cons              -0.287          -0.060          -0.305   \n                  (0.242)         (0.103)         (0.370)   \n------------------------------------------------------------\nr2_w                0.016           0.011           0.007   \nr2_b                0.206           0.119           0.104   \nr2_o                0.028           0.017           0.011   \nN                 589.000         703.000         684.000   \nN_g                31.000          37.000          36.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"NZ\" & stimtype==\"single photo\" , re \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"RU\" & stimtype==\"single photo\" , re \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"SE\" & stimtype==\"single photo\" , re \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"SW\" & stimtype==\"single photo\" , re \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"UK\" & stimtype==\"single photo\" , re \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age \n> income university if country2==\"US\" & stimtype==\"single photo\" , re \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.018           0.033***       -0.005   \n                  (0.010)         (0.010)         (0.004)   \nideo_right~x       -0.042           0.158*         -0.055   \n                  (0.079)         (0.072)         (0.031)   \nc.neg#c.id~x        0.007          -0.036**         0.013*  \n                  (0.014)         (0.014)         (0.006)   \npho_order           0.002          -0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.031          -0.008           0.015   \n                  (0.047)         (0.031)         (0.014)   \nage                -0.001          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome              0.032          -0.055          -0.045   \n                  (0.067)         (0.080)         (0.043)   \nuniversity         -0.033          -0.040           0.002   \n                  (0.041)         (0.049)         (0.014)   \n_cons              -0.061          -0.031           0.032   \n                  (0.096)         (0.097)         (0.041)   \n------------------------------------------------------------\nr2_w                0.017           0.020           0.008   \nr2_b                0.094           0.102           0.117   \nr2_o                0.022           0.024           0.010   \nN                 608.000         608.000         912.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.008           0.007           0.009   \n                  (0.010)         (0.009)         (0.006)   \nideo_right~x       -0.112          -0.011          -0.013   \n                  (0.069)         (0.066)         (0.050)   \nc.neg#c.id~x        0.012          -0.006           0.002   \n                  (0.013)         (0.013)         (0.010)   \npho_order          -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nfemale              0.059           0.048           0.004   \n                  (0.031)         (0.030)         (0.022)   \nage                 0.002          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nincome              0.030          -0.072           0.048   \n                  (0.085)         (0.058)         (0.045)   \nuniversity          0.018          -0.059           0.019   \n                  (0.033)         (0.040)         (0.023)   \n_cons              -0.157           0.031          -0.051   \n                  (0.084)         (0.078)         (0.057)   \n------------------------------------------------------------\nr2_w                0.010           0.002           0.002   \nr2_b                0.279           0.186           0.033   \nr2_o                0.026           0.012           0.003   \nN                 586.000         907.000        2641.000   \nN_g                31.000          48.000         139.000   \n------------------------------------------------------------\n. * Table A8 Row 2\n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(56,936 real changes made, 17,708 to missing)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 , re \n.   estimates store A\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 & wp_right2_ext==1, re \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if stimtype==\"single video\" & local==0 & political_interest_dichox==1, re \n.   estimates store C\n.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.017           0.001          -0.049   \n                  (0.022)         (0.026)         (0.029)   \nwp_right2           0.063           0.050           0.079   \n                  (0.052)         (0.058)         (0.067)   \nc.neg#c.wp~2        0.045           0.073           0.152*  \n                  (0.048)         (0.055)         (0.064)   \nvid_order          -0.074***       -0.073***       -0.072***\n                  (0.005)         (0.007)         (0.007)   \nfemale             -0.027          -0.027          -0.040   \n                  (0.023)         (0.031)         (0.033)   \nage                 0.001           0.001          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nincome              0.016           0.112          -0.061   \n                  (0.049)         (0.063)         (0.069)   \nuniversity         -0.021          -0.023          -0.058   \n                  (0.025)         (0.033)         (0.037)   \n_cons               0.215***        0.157*          0.306***\n                  (0.055)         (0.072)         (0.077)   \n------------------------------------------------------------\nr2_w                0.050           0.049           0.047   \nr2_b                0.037           0.042           0.052   \nr2_o                0.046           0.047           0.047   \nN                4665.000        2525.000        2220.000   \nN_g               933.000         505.000         444.000   \n------------------------------------------------------------\n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 & wp_right2_ext=\n> =1, re  \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 & wp_right2_ext=\n> =1, re  \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store G\n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.225          -0.015          -0.112   \n                  (0.200)         (0.157)         (0.069)   \nwp_right2          -0.387          -0.062          -0.164   \n                  (0.396)         (0.854)         (0.194)   \nc.neg#c.wp~2        0.325           0.601           0.147   \n                  (0.416)         (0.422)         (0.177)   \nvid_order          -0.117*         -0.253***       -0.069** \n                  (0.047)         (0.050)         (0.022)   \nfemale             -0.076           0.368          -0.000   \n                  (0.244)         (0.402)         (0.129)   \nage                 0.014           0.081           0.000   \n                  (0.018)         (0.076)         (0.004)   \nincome              0.119          -0.473           0.450   \n                  (0.640)         (0.841)         (0.231)   \nuniversity         -0.024          -0.138          -0.101   \n                  (0.235)         (0.649)         (0.114)   \n_cons               0.337          -0.855           0.090   \n                  (0.588)         (1.750)         (0.268)   \n------------------------------------------------------------\nr2_w                0.078           0.339           0.152   \nr2_b                0.502           0.179           0.384   \nr2_o                0.109           0.280           0.222   \nN                  85.000          80.000          80.000   \nN_g                17.000          16.000          16.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.088          -0.090          -0.033   \n                  (0.127)         (0.194)         (0.075)   \nwp_right2           0.873           0.049          -0.018   \n                  (0.524)         (0.429)         (0.228)   \nc.neg#c.wp~2       -0.080           0.240           0.250   \n                  (0.314)         (0.374)         (0.191)   \nvid_order          -0.140***       -0.112***       -0.051*  \n                  (0.038)         (0.027)         (0.021)   \nfemale              0.152          -0.018          -0.016   \n                  (0.246)         (0.132)         (0.098)   \nage                 0.014          -0.003          -0.001   \n                  (0.010)         (0.013)         (0.003)   \nincome              0.285           0.262           0.020   \n                  (0.634)         (0.307)         (0.204)   \nuniversity          0.444          -0.196          -0.052   \n                  (0.267)         (0.213)         (0.100)   \n_cons              -1.030           0.565           0.226   \n                  (0.636)         (0.425)         (0.237)   \n------------------------------------------------------------\nr2_w                0.156           0.080           0.126   \nr2_b                0.415           0.183           0.064   \nr2_o                0.230           0.089           0.113   \nN                  95.000         210.000          90.000   \nN_g                19.000          42.000          18.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 & wp_right2_ext=\n> =1, re  \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 & wp_right2_ext=\n> =1, re  \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.013           0.141           0.121   \n                  (0.167)         (0.096)         (0.128)   \nwp_right2           0.729          -0.066          -0.262   \n                  (0.623)         (0.180)         (0.267)   \nc.neg#c.wp~2        0.261          -0.143          -0.198   \n                  (0.373)         (0.147)         (0.197)   \nvid_order          -0.092*         -0.057***       -0.099***\n                  (0.046)         (0.016)         (0.027)   \nfemale             -0.363          -0.177          -0.119   \n                  (0.248)         (0.093)         (0.123)   \nage                -0.021          -0.001           0.008   \n                  (0.012)         (0.004)         (0.010)   \nincome              1.086           0.113          -0.052   \n                  (0.604)         (0.128)         (0.314)   \nuniversity         -0.297           0.031          -0.046   \n                  (0.230)         (0.094)         (0.160)   \n_cons               0.523           0.324           0.247   \n                  (0.504)         (0.185)         (0.368)   \n------------------------------------------------------------\nr2_w                0.057           0.097           0.103   \nr2_b                0.323           0.291           0.249   \nr2_o                0.126           0.149           0.133   \nN                 115.000         165.000         140.000   \nN_g                23.000          33.000          28.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.084          -0.050          -0.008   \n                  (0.084)         (0.214)         (0.057)   \nwp_right2           0.525          -0.081           0.114   \n                  (0.366)         (0.532)         (0.199)   \nc.neg#c.wp~2        0.281           0.324          -0.001   \n                  (0.259)         (0.513)         (0.186)   \nvid_order          -0.082**        -0.041          -0.040*  \n                  (0.027)         (0.062)         (0.018)   \nfemale              0.075          -0.154          -0.146   \n                  (0.143)         (0.264)         (0.076)   \nage                 0.007           0.084          -0.001   \n                  (0.024)         (0.142)         (0.020)   \nincome             -0.059           0.617           0.567** \n                  (0.324)         (0.917)         (0.208)   \nuniversity         -0.129          -0.077           0.352*  \n                  (0.198)         (0.621)         (0.178)   \n_cons              -0.099          -1.628          -0.390   \n                  (0.738)         (3.123)         (0.561)   \n------------------------------------------------------------\nr2_w                0.049           0.012           0.058   \nr2_b                0.165           0.268           0.455   \nr2_o                0.079           0.035           0.151   \nN                 210.000          80.000          95.000   \nN_g                42.000          16.000          19.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 & wp_right2_ext==1\n> , re  \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.036           0.004           0.084          -0.138   \n                  (0.196)         (0.084)         (0.168)         (0.084)   \nwp_right2          -0.185           0.215           0.139           0.024   \n                  (0.625)         (0.278)         (0.282)         (0.171)   \nc.neg#c.wp~2        0.062           0.158          -0.110           0.193   \n                  (0.498)         (0.204)         (0.278)         (0.132)   \nvid_order          -0.088          -0.059*         -0.098*         -0.029   \n                  (0.051)         (0.024)         (0.040)         (0.015)   \nfemale              0.189          -0.019           0.104           0.078   \n                  (0.234)         (0.127)         (0.155)         (0.079)   \nage                -0.099          -0.006           0.009           0.004   \n                  (0.082)         (0.004)         (0.009)         (0.004)   \nincome             -0.325          -0.088           0.118           0.211   \n                  (0.401)         (0.226)         (0.334)         (0.200)   \nuniversity          0.286           0.190          -0.146           0.020   \n                  (0.581)         (0.152)         (0.343)         (0.079)   \n_cons               2.290           0.336           0.000          -0.117   \n                  (1.742)         (0.231)             (.)         (0.228)   \n----------------------------------------------------------------------------\nr2_w                0.037           0.058           0.082           0.048   \nr2_b                0.324           0.473           0.305           0.206   \nr2_o                0.089           0.121           0.115           0.087   \nN                  85.000          95.000          85.000         125.000   \nN_g                17.000          19.000          17.000          25.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.069          -0.179*          0.063   \n                  (0.077)         (0.074)         (0.064)   \nwp_right2           0.244          -0.335           0.106   \n                  (0.187)         (0.251)         (0.160)   \nc.neg#c.wp~2        0.182           0.417*         -0.017   \n                  (0.160)         (0.201)         (0.138)   \nvid_order          -0.028          -0.057*         -0.036*  \n                  (0.024)         (0.022)         (0.016)   \nfemale             -0.148          -0.087          -0.034   \n                  (0.168)         (0.109)         (0.079)   \nage                -0.007           0.001           0.001   \n                  (0.005)         (0.004)         (0.003)   \nincome             -0.789**         0.373           0.124   \n                  (0.271)         (0.267)         (0.156)   \nuniversity          0.112           0.020           0.099   \n                  (0.111)         (0.143)         (0.083)   \n_cons               0.752*          0.196          -0.071   \n                  (0.322)         (0.228)         (0.174)   \n------------------------------------------------------------\nr2_w                0.059           0.115           0.018   \nr2_b                0.547           0.124           0.036   \nr2_o                0.195           0.116           0.022   \nN                  75.000         120.000         495.000   \nN_g                15.000          24.000          99.000   \n------------------------------------------------------------\n.   \n.   xtset resp vid_order\n       panel variable:  resp (unbalanced)\n        time variable:  vid_order, 1 to 7\n                delta:  1 unit\n.   replace neg = v_negativity\n(0 real changes made)\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"BR\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store B\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.e\" & stimtype==\"single video\" & local==0 & political_inte\n> rest_dichox==1, re  \n.   estimates store C\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CA.f\" & stimtype==\"single video\" & local==0 & political_inte\n> rest_dichox==1, re  \n.   estimates store D\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CH\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store E\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"CN\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store F\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"DK\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store G\n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.025          -0.298          -0.073   \n                  (0.231)         (0.202)         (0.066)   \nwp_right2          -0.004           3.571*         -0.262   \n                  (0.614)         (1.615)         (0.227)   \nc.neg#c.wp~2       -0.069           1.078           0.107   \n                  (0.550)         (1.646)         (0.205)   \nvid_order          -0.039          -0.141**        -0.043*  \n                  (0.051)         (0.052)         (0.021)   \nfemale              0.048          -0.696*         -0.048   \n                  (0.243)         (0.292)         (0.113)   \nage                 0.015           0.006          -0.002   \n                  (0.021)         (0.028)         (0.004)   \nincome             -0.107           0.404           0.000   \n                  (0.500)         (0.573)         (0.212)   \nuniversity          0.161           0.160          -0.057   \n                  (0.259)         (0.590)         (0.115)   \n_cons              -0.284          -0.191           0.361   \n                  (0.616)         (1.158)         (0.243)   \n------------------------------------------------------------\nr2_w                0.016           0.163           0.055   \nr2_b                0.058           0.730           0.077   \nr2_o                0.019           0.290           0.060   \nN                  95.000          55.000         125.000   \nN_g                19.000          11.000          25.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.026          -0.094          -0.033   \n                  (0.186)         (0.187)         (0.099)   \nwp_right2           0.199           0.455           0.104   \n                  (0.674)         (0.425)         (0.332)   \nc.neg#c.wp~2        0.290           0.304           0.213   \n                  (0.505)         (0.368)         (0.273)   \nvid_order          -0.141**        -0.088***       -0.040   \n                  (0.049)         (0.025)         (0.025)   \nfemale             -0.303          -0.151          -0.004   \n                  (0.333)         (0.126)         (0.159)   \nage                 0.007          -0.020          -0.004   \n                  (0.013)         (0.012)         (0.003)   \nincome             -1.522           0.220           0.583*  \n                  (1.099)         (0.299)         (0.253)   \nuniversity          0.475          -0.375*          0.005   \n                  (0.404)         (0.155)         (0.134)   \n_cons               0.464           0.946*         -0.113   \n                  (0.713)         (0.404)         (0.250)   \n------------------------------------------------------------\nr2_w                0.127           0.071           0.059   \nr2_b                0.349           0.349           0.435   \nr2_o                0.177           0.116           0.140   \nN                  75.000         200.000          80.000   \nN_g                15.000          40.000          16.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"FR\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store H\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"GH\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store I\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IN\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store J\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.j\" & stimtype==\"single video\" & local==0 & political_inte\n> rest_dichox==1, re  \n.   estimates store K\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IS.p\" & stimtype==\"single video\" & local==0 & political_inte\n> rest_dichox==1, re  \n.   estimates store L\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"IT\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store M\n.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.193           0.214          -0.113   \n                  (0.202)         (0.135)         (0.123)   \nwp_right2          -1.711*         -0.058          -0.466   \n                  (0.736)         (0.183)         (0.272)   \nc.neg#c.wp~2        0.598          -0.286           0.256   \n                  (0.457)         (0.200)         (0.185)   \nvid_order          -0.095*         -0.045**        -0.117***\n                  (0.042)         (0.016)         (0.022)   \nfemale             -0.033          -0.128          -0.096   \n                  (0.243)         (0.078)         (0.172)   \nage                 0.015           0.005          -0.000   \n                  (0.011)         (0.005)         (0.008)   \nincome              0.160           0.243*         -0.162   \n                  (0.446)         (0.124)         (0.294)   \nuniversity         -0.178          -0.054          -0.092   \n                  (0.233)         (0.075)         (0.142)   \n_cons               0.760          -0.009           0.817*  \n                  (0.494)         (0.242)         (0.327)   \n------------------------------------------------------------\nr2_w                0.106           0.072           0.217   \nr2_b                0.402           0.433           0.274   \nr2_o                0.177           0.153           0.231   \nN                  90.000         140.000         130.000   \nN_g                18.000          28.000          26.000   \n------------------------------------------------------------\n.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.140          -0.235           0.016   \n                  (0.099)         (0.273)         (0.097)   \nwp_right2           0.339           0.028          -0.058   \n                  (0.511)         (0.782)         (0.396)   \nc.neg#c.wp~2        0.364           0.797           0.160   \n                  (0.407)         (0.751)         (0.359)   \nvid_order          -0.127***       -0.034          -0.066*  \n                  (0.031)         (0.053)         (0.028)   \nfemale             -0.137           0.124          -0.197   \n                  (0.169)         (0.245)         (0.119)   \nage                -0.018          -0.014           0.006   \n                  (0.028)         (0.051)         (0.007)   \nincome             -0.700*         -0.102           1.177***\n                  (0.351)         (0.581)         (0.338)   \nuniversity         -0.492*         -0.233           0.406*  \n                  (0.233)         (0.537)         (0.194)   \n_cons               1.615           0.543          -0.655   \n                  (0.829)         (1.198)         (0.390)   \n------------------------------------------------------------\nr2_w                0.072           0.022           0.138   \nr2_b                0.263           0.053           0.723   \nr2_o                0.129           0.024           0.282   \nN                 235.000          95.000          65.000   \nN_g                47.000          19.000          13.000   \n------------------------------------------------------------\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"JP\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store N\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"NZ\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store O\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"RU\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store P\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SE\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store Q\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"SW\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store R \n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"UK\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store S\n.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi\n> ty if country2==\"US\" & stimtype==\"single video\" & local==0 & political_intere\n> st_dichox==1, re  \n.   estimates store T\n.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                    gslmc           gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.088          -0.088           0.300          -0.124   \n                  (0.257)         (0.092)         (0.230)         (0.096)   \nwp_right2           0.270           0.143           0.242           0.210   \n                  (0.839)         (0.272)         (0.350)         (0.219)   \nc.neg#c.wp~2        0.107           0.154          -0.377           0.206   \n                  (0.704)         (0.230)         (0.342)         (0.168)   \nvid_order          -0.100          -0.088***       -0.083*         -0.031*  \n                  (0.059)         (0.024)         (0.042)         (0.015)   \nfemale              0.658*         -0.169           0.241           0.008   \n                  (0.330)         (0.124)         (0.170)         (0.083)   \nage                -0.061          -0.004           0.005           0.002   \n                  (0.085)         (0.003)         (0.007)         (0.004)   \nincome              0.566           0.124           0.100           0.442   \n                  (0.617)         (0.240)         (0.397)         (0.271)   \nuniversity          1.076          -0.051          -0.225           0.053   \n                  (2.170)         (0.141)         (0.338)         (0.086)   \n_cons               0.000           0.488          -0.021          -0.261   \n                      (.)         (0.268)         (0.526)         (0.285)   \n----------------------------------------------------------------------------\nr2_w                0.036           0.170           0.071           0.045   \nr2_b                0.503           0.391           0.620           0.203   \nr2_o                0.114           0.209           0.133           0.084   \nN                  85.000         100.000          80.000         135.000   \nN_g                17.000          20.000          16.000          27.000   \n----------------------------------------------------------------------------\n.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                    gslmc           gslmc           gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.042          -0.043          -0.010   \n                  (0.088)         (0.091)         (0.073)   \nwp_right2           0.021          -0.293           0.139   \n                  (0.239)         (0.371)         (0.206)   \nc.neg#c.wp~2        0.114           0.173           0.065   \n                  (0.213)         (0.282)         (0.173)   \nvid_order          -0.013          -0.073**        -0.032   \n                  (0.028)         (0.023)         (0.018)   \nfemale              0.214           0.017          -0.037   \n                  (0.162)         (0.125)         (0.081)   \nage                 0.003          -0.003           0.003   \n                  (0.004)         (0.006)         (0.003)   \nincome             -0.754*          0.058          -0.345*  \n                  (0.313)         (0.333)         (0.167)   \nuniversity         -0.145          -0.171           0.238*  \n                  (0.132)         (0.159)         (0.095)   \n_cons               0.382           0.451          -0.038   \n                  (0.280)         (0.305)         (0.182)   \n------------------------------------------------------------\nr2_w                0.021           0.153           0.009   \nr2_b                0.760           0.209           0.215   \nr2_o                0.207           0.161           0.065   \nN                  55.000          80.000         300.000   \nN_g                11.000          16.000          60.000   \n------------------------------------------------------------\n.       \n.          \n. * Table A8 Row 5\n.                                   \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(56,936 real changes made, 39,228 to missing)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" , re \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & wp_right2_ext==1, re \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & political_interest_dichox==1, re \n.   estimates store C\n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.008*          0.010*  \n                  (0.003)         (0.004)         (0.005)   \nwp_right2           0.050           0.022           0.048   \n                  (0.037)         (0.041)         (0.050)   \nc.neg#c.wp~2       -0.012          -0.006          -0.011   \n                  (0.007)         (0.008)         (0.010)   \npho_order           0.002***        0.003***        0.002** \n                  (0.000)         (0.001)         (0.001)   \nfemale              0.012           0.012           0.028** \n                  (0.007)         (0.009)         (0.011)   \nage                -0.000          -0.000          -0.001   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.018          -0.021          -0.032   \n                  (0.015)         (0.019)         (0.022)   \nuniversity          0.006           0.010           0.014   \n                  (0.007)         (0.010)         (0.011)   \n_cons              -0.070**        -0.058*         -0.063   \n                  (0.023)         (0.028)         (0.032)   \n------------------------------------------------------------\nr2_w                0.003           0.003           0.002   \nr2_b                0.015           0.022           0.046   \nr2_o                0.003           0.003           0.005   \nN               15263.000        8184.000        7139.000   \nN_g               804.000         431.000         376.000   \n------------------------------------------------------------\n.         \n.         \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & wp_right2_ext==1, re  \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & wp_right2_ext==1, r\n> e  \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.008*          0.012           0.008   \n                  (0.004)         (0.023)         (0.018)   \nwp_right2           0.022          -0.081           0.056   \n                  (0.041)         (0.259)         (0.254)   \nc.neg#c.wp~2       -0.006          -0.001           0.008   \n                  (0.008)         (0.049)         (0.044)   \npho_order           0.003***        0.008*          0.004   \n                  (0.001)         (0.004)         (0.004)   \nfemale              0.012          -0.005           0.008   \n                  (0.009)         (0.089)         (0.104)   \nage                -0.000          -0.002           0.001   \n                  (0.000)         (0.007)         (0.003)   \nincome             -0.021           0.033          -0.171   \n                  (0.019)         (0.171)         (0.184)   \nuniversity          0.010          -0.016           0.128   \n                  (0.010)         (0.064)         (0.091)   \n_cons              -0.058*         -0.119          -0.178   \n                  (0.028)         (0.227)         (0.213)   \n------------------------------------------------------------\nr2_w                0.003           0.022           0.007   \nr2_b                0.022           0.162           0.288   \nr2_o                0.003           0.025           0.033   \nN                8184.000         302.000         304.000   \nN_g               431.000          16.000          16.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.006          -0.010          -0.005   \n                  (0.014)         (0.027)         (0.011)   \nwp_right2          -0.177          -0.163          -0.109   \n                  (0.191)         (0.285)         (0.149)   \nc.neg#c.wp~2        0.036           0.029           0.010   \n                  (0.035)         (0.053)         (0.028)   \npho_order           0.001           0.002           0.004*  \n                  (0.003)         (0.003)         (0.002)   \nfemale             -0.028           0.068          -0.073*  \n                  (0.050)         (0.045)         (0.031)   \nage                -0.000          -0.000          -0.001   \n                  (0.002)         (0.004)         (0.001)   \nincome              0.002           0.107          -0.008   \n                  (0.127)         (0.114)         (0.065)   \nuniversity         -0.015           0.041          -0.018   \n                  (0.054)         (0.073)         (0.032)   \n_cons               0.063          -0.079           0.061   \n                  (0.144)         (0.193)         (0.088)   \n------------------------------------------------------------\nr2_w                0.004           0.001           0.012   \nr2_b                0.062           0.148           0.412   \nr2_o                0.005           0.008           0.029   \nN                 361.000         779.000         342.000   \nN_g                19.000          41.000          18.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & wp_right2_ext==1, r\n> e  \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & wp_right2_ext==1, r\n> e  \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.022           0.015           0.009           0.003   \n                  (0.016)         (0.015)         (0.021)         (0.014)   \nwp_right2           0.190          -0.034           0.080          -0.052   \n                  (0.211)         (0.119)         (0.168)         (0.226)   \nc.neg#c.wp~2       -0.027          -0.009          -0.020          -0.013   \n                  (0.037)         (0.023)         (0.032)         (0.033)   \npho_order           0.007*          0.002           0.001           0.003   \n                  (0.003)         (0.002)         (0.003)         (0.002)   \nfemale              0.006           0.062*          0.017          -0.051   \n                  (0.049)         (0.028)         (0.039)         (0.043)   \nage                 0.001           0.001          -0.002          -0.011   \n                  (0.002)         (0.001)         (0.003)         (0.007)   \nincome             -0.043          -0.046           0.029          -0.118   \n                  (0.120)         (0.039)         (0.104)         (0.105)   \nuniversity          0.077          -0.031          -0.014           0.022   \n                  (0.046)         (0.029)         (0.050)         (0.056)   \n_cons              -0.287*         -0.073          -0.018           0.308   \n                  (0.124)         (0.090)         (0.153)         (0.263)   \n----------------------------------------------------------------------------\nr2_w                0.021           0.009           0.001           0.009   \nr2_b                0.354           0.395           0.042           0.423   \nr2_o                0.031           0.033           0.002           0.037   \nN                 437.000         627.000         512.000         266.000   \nN_g                23.000          33.000          27.000          14.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.052*          0.005           0.032   \n                  (0.021)         (0.011)         (0.030)   \nwp_right2          -0.255          -0.022           0.126   \n                  (0.253)         (0.184)         (0.399)   \nc.neg#c.wp~2        0.066          -0.003          -0.018   \n                  (0.048)         (0.036)         (0.074)   \npho_order           0.011**         0.003          -0.000   \n                  (0.004)         (0.002)         (0.005)   \nfemale             -0.116          -0.032           0.026   \n                  (0.061)         (0.033)         (0.080)   \nage                 0.049          -0.005           0.028   \n                  (0.033)         (0.009)         (0.028)   \nincome              0.115           0.075          -0.048   \n                  (0.213)         (0.090)         (0.138)   \nuniversity         -0.835           0.022           0.054   \n                  (0.671)         (0.076)         (0.200)   \n_cons               0.000           0.042          -0.719   \n                      (.)         (0.246)         (0.617)   \n------------------------------------------------------------\nr2_w                0.057           0.007           0.008   \nr2_b                0.331           0.163           0.307   \nr2_o                0.081           0.013           0.014   \nN                 285.000         361.000         323.000   \nN_g                15.000          19.000          17.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & wp_right2_ext==1, re \n>  \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.060***        0.059**        -0.007   \n                  (0.017)         (0.022)         (0.012)   \nwp_right2           0.323           0.428*         -0.074   \n                  (0.236)         (0.188)         (0.094)   \nc.neg#c.wp~2       -0.101*         -0.075*          0.014   \n                  (0.042)         (0.036)         (0.018)   \npho_order          -0.003           0.002           0.001   \n                  (0.003)         (0.003)         (0.001)   \nfemale              0.010          -0.065           0.017   \n                  (0.062)         (0.050)         (0.020)   \nage                 0.001          -0.004          -0.000   \n                  (0.002)         (0.003)         (0.001)   \nincome              0.109          -0.140          -0.028   \n                  (0.111)         (0.106)         (0.051)   \nuniversity         -0.137          -0.181           0.001   \n                  (0.075)         (0.145)         (0.020)   \n_cons              -0.202           0.000           0.020   \n                  (0.140)             (.)         (0.080)   \n------------------------------------------------------------\nr2_w                0.037           0.025           0.004   \nr2_b                0.382           0.301           0.150   \nr2_o                0.055           0.037           0.006   \nN                 361.000         323.000         475.000   \nN_g                19.000          17.000          25.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.003           0.009           0.004   \n                  (0.015)         (0.010)         (0.012)   \nwp_right2          -0.139           0.110           0.068   \n                  (0.169)         (0.136)         (0.140)   \nc.neg#c.wp~2        0.030          -0.025          -0.010   \n                  (0.032)         (0.026)         (0.027)   \npho_order          -0.000           0.001           0.002   \n                  (0.003)         (0.002)         (0.002)   \nfemale              0.006           0.010           0.025   \n                  (0.075)         (0.030)         (0.029)   \nage                -0.001          -0.000          -0.001   \n                  (0.002)         (0.001)         (0.001)   \nincome             -0.033          -0.105           0.015   \n                  (0.121)         (0.073)         (0.059)   \nuniversity          0.017          -0.020           0.029   \n                  (0.049)         (0.039)         (0.031)   \n_cons               0.044          -0.002          -0.061   \n                  (0.160)         (0.080)         (0.082)   \n------------------------------------------------------------\nr2_w                0.011           0.004           0.001   \nr2_b                0.373           0.201           0.050   \nr2_o                0.014           0.010           0.003   \nN                 284.000         455.000        1387.000   \nN_g                15.000          24.000          73.000   \n------------------------------------------------------------\n.                             \n.   xtset resp pho_order\n       panel variable:  resp (unbalanced)\n        time variable:  pho_order, 2 to 26\n                delta:  1 unit\n.   replace neg = p_negativity\n(0 real changes made)\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if stimtype==\"single photo\" & political_interest_dichox==1, re  \n.   estimates store A\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"BR\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store B\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CA.f\" & stimtype==\"single photo\" & political_interest_\n> dichox==1, re  \n.   estimates store D\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CH\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store E\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"CN\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store F\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"DK\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store G\n.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.008           0.006   \n                  (0.005)         (0.023)         (0.014)   \nwp_right2           0.048           0.027           0.003   \n                  (0.050)         (0.300)         (0.241)   \nc.neg#c.wp~2       -0.011          -0.014           0.022   \n                  (0.010)         (0.056)         (0.044)   \npho_order           0.002**         0.007*          0.006*  \n                  (0.001)         (0.003)         (0.003)   \nfemale              0.028**        -0.023           0.079   \n                  (0.011)         (0.061)         (0.068)   \nage                -0.001          -0.003           0.000   \n                  (0.000)         (0.005)         (0.002)   \nincome             -0.032          -0.088          -0.146   \n                  (0.022)         (0.133)         (0.127)   \nuniversity          0.014          -0.009           0.109   \n                  (0.011)         (0.068)         (0.069)   \n_cons              -0.063           0.014          -0.190   \n                  (0.032)         (0.190)         (0.151)   \n------------------------------------------------------------\nr2_w                0.002           0.014           0.016   \nr2_b                0.046           0.193           0.224   \nr2_o                0.005           0.019           0.033   \nN                7139.000         341.000         475.000   \nN_g               376.000          18.000          25.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.005          -0.020           0.002   \n                  (0.025)         (0.027)         (0.011)   \nwp_right2          -0.289          -0.354          -0.239   \n                  (0.362)         (0.291)         (0.169)   \nc.neg#c.wp~2        0.054           0.054           0.044   \n                  (0.069)         (0.054)         (0.031)   \npho_order          -0.000           0.003           0.002   \n                  (0.004)         (0.003)         (0.002)   \nfemale              0.105           0.097*         -0.031   \n                  (0.088)         (0.045)         (0.043)   \nage                 0.001           0.001          -0.001   \n                  (0.003)         (0.004)         (0.001)   \nincome              0.158           0.145           0.039   \n                  (0.288)         (0.116)         (0.068)   \nuniversity         -0.084           0.060          -0.022   \n                  (0.104)         (0.055)         (0.037)   \n_cons              -0.132          -0.095           0.016   \n                  (0.215)         (0.191)         (0.083)   \n------------------------------------------------------------\nr2_w                0.009           0.004           0.029   \nr2_b                0.312           0.229           0.446   \nr2_o                0.016           0.016           0.036   \nN                 285.000         741.000         304.000   \nN_g                15.000          39.000          16.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"FR\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store H\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"GH\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store I\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IN\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store J\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.j\" & stimtype==\"single photo\" & political_interest_\n> dichox==1, re  \n.   estimates store K\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IS.p\" & stimtype==\"single photo\" & political_interest_\n> dichox==1, re  \n.   estimates store L\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"IT\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store M\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"JP\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store N\n.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.038           0.027          -0.019           0.003   \n                  (0.025)         (0.023)         (0.025)         (0.023)   \nwp_right2           0.303           0.090          -0.115          -0.167   \n                  (0.324)         (0.179)         (0.195)         (0.528)   \nc.neg#c.wp~2       -0.039          -0.036           0.012           0.093   \n                  (0.059)         (0.035)         (0.038)         (0.088)   \npho_order           0.002           0.004*          0.001          -0.004   \n                  (0.003)         (0.002)         (0.003)         (0.005)   \nfemale              0.004           0.066           0.026          -0.088   \n                  (0.060)         (0.035)         (0.054)         (0.176)   \nage                -0.002          -0.001          -0.003           0.005   \n                  (0.003)         (0.002)         (0.002)         (0.011)   \nincome             -0.112          -0.065          -0.059          -0.060   \n                  (0.110)         (0.056)         (0.093)         (0.183)   \nuniversity          0.082          -0.015           0.022          -0.113   \n                  (0.058)         (0.034)         (0.044)         (0.333)   \n_cons              -0.181          -0.085           0.192           0.000   \n                  (0.169)         (0.155)         (0.157)             (.)   \n----------------------------------------------------------------------------\nr2_w                0.015           0.013           0.005           0.022   \nr2_b                0.362           0.352           0.138           0.213   \nr2_o                0.032           0.036           0.010           0.030   \nN                 342.000         532.000         475.000         171.000   \nN_g                18.000          28.000          25.000           9.000   \n----------------------------------------------------------------------------\n.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.075*          0.002           0.050   \n                  (0.030)         (0.017)         (0.035)   \nwp_right2          -0.832           0.043           0.412   \n                  (0.448)         (0.330)         (0.512)   \nc.neg#c.wp~2        0.156          -0.003          -0.114   \n                  (0.081)         (0.063)         (0.095)   \npho_order           0.006           0.007*         -0.006   \n                  (0.004)         (0.003)         (0.005)   \nfemale             -0.056          -0.051           0.128   \n                  (0.077)         (0.048)         (0.108)   \nage                 0.004          -0.003           0.011   \n                  (0.016)         (0.003)         (0.028)   \nincome             -0.263           0.101           0.127   \n                  (0.183)         (0.136)         (0.203)   \nuniversity          0.380          -0.037          -0.399   \n                  (0.377)         (0.079)         (0.724)   \n_cons               0.000          -0.045           0.000   \n                      (.)         (0.173)             (.)   \n------------------------------------------------------------\nr2_w                0.032           0.026           0.011   \nr2_b                0.224           0.705           0.320   \nr2_o                0.050           0.041           0.018   \nN                 342.000         247.000         323.000   \nN_g                18.000          13.000          17.000   \n------------------------------------------------------------\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"NZ\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store O\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"RU\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store P\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SE\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store Q\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"SW\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store R \n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"UK\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store S\n.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un\n> iversity if country2==\"US\" & stimtype==\"single photo\" & political_interest_di\n> chox==1, re  \n.   estimates store T\n.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.022           0.077**        -0.008   \n                  (0.014)         (0.028)         (0.014)   \nwp_right2           0.186           0.501*         -0.061   \n                  (0.189)         (0.214)         (0.125)   \nc.neg#c.wp~2       -0.048          -0.101*          0.020   \n                  (0.036)         (0.042)         (0.024)   \npho_order           0.003          -0.002           0.002   \n                  (0.002)         (0.003)         (0.001)   \nfemale              0.005           0.035           0.007   \n                  (0.044)         (0.050)         (0.022)   \nage                -0.002          -0.002          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nincome             -0.037          -0.137          -0.015   \n                  (0.084)         (0.116)         (0.073)   \nuniversity          0.045          -0.022          -0.001   \n                  (0.050)         (0.099)         (0.023)   \n_cons              -0.064          -0.257           0.011   \n                  (0.115)         (0.194)         (0.100)   \n------------------------------------------------------------\nr2_w                0.011           0.026           0.008   \nr2_b                0.274           0.295           0.060   \nr2_o                0.021           0.036           0.008   \nN                 380.000         304.000         513.000   \nN_g                20.000          16.000          27.000   \n------------------------------------------------------------\n.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n              p_gslmc_all     p_gslmc_all     p_gslmc_all   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009          -0.005           0.020   \n                  (0.014)         (0.012)         (0.018)   \nwp_right2          -0.149          -0.002           0.187   \n                  (0.182)         (0.183)         (0.247)   \nc.neg#c.wp~2        0.007          -0.001          -0.023   \n                  (0.035)         (0.033)         (0.045)   \npho_order          -0.001           0.004          -0.001   \n                  (0.003)         (0.002)         (0.003)   \nfemale              0.004           0.013           0.041   \n                  (0.060)         (0.036)         (0.048)   \nage                 0.002           0.000          -0.002   \n                  (0.002)         (0.002)         (0.002)   \nincome              0.051          -0.034          -0.023   \n                  (0.115)         (0.095)         (0.107)   \nuniversity         -0.027          -0.033           0.038   \n                  (0.048)         (0.046)         (0.057)   \n_cons              -0.093          -0.026          -0.079   \n                  (0.118)         (0.103)         (0.133)   \n------------------------------------------------------------\nr2_w                0.009           0.016           0.003   \nr2_b                0.464           0.111           0.060   \nr2_o                0.020           0.019           0.007   \nN                 208.000         301.000         836.000   \nN_g                11.000          16.000          44.000   \n------------------------------------------------------------\n.   \n"} -->
<pre><code>. *** Syntax for analyses of stimulus-level data
. *** Use data file 'Stimulus-data.dta' with this syntax
. * Table 3
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(39,228 real changes made)
.   quietly xtreg gslmc neg vid_order female age income university if stimtype=
&gt; =&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc neg vid_order female age income university if wp_right2
&gt; _dichox==0 &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc neg vid_order female age income university if wp_right2
&gt; _dichox==1 &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G  
.   esttab D E F G , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b
&gt;  r2_o N N_g)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.034**         0.028           0.041**         0.017   
                  (0.011)         (0.016)         (0.015)         (0.022)   
vid_order          -0.074***       -0.077***       -0.070***       -0.074***
                  (0.005)         (0.007)         (0.007)         (0.005)   
female             -0.028          -0.032          -0.020          -0.027   
                  (0.023)         (0.034)         (0.032)         (0.023)   
age                 0.001           0.001           0.001           0.001   
                  (0.001)         (0.002)         (0.001)         (0.001)   
income              0.013           0.028          -0.006           0.016   
                  (0.049)         (0.069)         (0.070)         (0.049)   
university         -0.026          -0.058           0.009          -0.021   
                  (0.024)         (0.036)         (0.034)         (0.025)   
wp_right2                                                           0.063   
                                                                  (0.052)   
c.neg#c.wp~2                                                        0.045   
                                                                  (0.048)   
_cons               0.243***        0.251***        0.234**         0.215***
                  (0.051)         (0.073)         (0.071)         (0.055)   
----------------------------------------------------------------------------
r2_w                0.050           0.049           0.051           0.050   
r2_b                0.035           0.041           0.031           0.037   
r2_o                0.045           0.047           0.045           0.046   
N                4665.000        2355.000        2310.000        4665.000   
N_g               933.000         471.000         462.000         933.000   
----------------------------------------------------------------------------
.       
. * Figure 3
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.036          -0.112          -0.078   
                  (0.139)         (0.101)         (0.061)   
wp_right2          -0.275          -0.112          -0.268   
                  (0.325)         (0.571)         (0.203)   
c.neg#c.wp~2        0.140           0.731*          0.134   
                  (0.338)         (0.341)         (0.188)   
vid_order          -0.071*         -0.122***       -0.042*  
                  (0.030)         (0.030)         (0.019)   
female             -0.083           0.188          -0.013   
                  (0.122)         (0.249)         (0.101)   
age                 0.013           0.025          -0.002   
                  (0.012)         (0.025)         (0.003)   
income              0.021          -0.201           0.050   
                  (0.281)         (0.443)         (0.197)   
university         -0.016          -0.167          -0.061   
                  (0.129)         (0.336)         (0.105)   
_cons               0.097          -0.176           0.326   
                  (0.349)         (0.779)         (0.228)   
------------------------------------------------------------
r2_w                0.048           0.152           0.059   
r2_b                0.121           0.085           0.077   
r2_o                0.057           0.129           0.063   
N                 175.000         160.000         135.000   
N_g                35.000          32.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.104          -0.086          -0.082   
                  (0.120)         (0.186)         (0.082)   
wp_right2           0.445          -0.112           0.067   
                  (0.481)         (0.383)         (0.252)   
c.neg#c.wp~2       -0.110           0.224           0.342   
                  (0.329)         (0.361)         (0.239)   
vid_order          -0.108***       -0.111***       -0.041*  
                  (0.029)         (0.023)         (0.019)   
female              0.170           0.006          -0.008   
                  (0.172)         (0.105)         (0.086)   
age                 0.005          -0.011           0.001   
                  (0.007)         (0.010)         (0.003)   
income              0.100           0.429           0.252   
                  (0.497)         (0.257)         (0.184)   
university          0.229          -0.133          -0.009   
                  (0.176)         (0.153)         (0.085)   
_cons              -0.341           0.668          -0.044   
                  (0.426)         (0.355)         (0.200)   
------------------------------------------------------------
r2_w                0.099           0.094           0.042   
r2_b                0.129           0.130           0.163   
r2_o                0.108           0.099           0.057   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.068           0.153           0.109   
                  (0.125)         (0.097)         (0.110)   
wp_right2          -0.090          -0.077          -0.236   
                  (0.394)         (0.161)         (0.209)   
c.neg#c.wp~2        0.077          -0.205          -0.176   
                  (0.311)         (0.149)         (0.172)   
vid_order          -0.119***       -0.067***       -0.087***
                  (0.026)         (0.012)         (0.018)   
female             -0.106          -0.124*         -0.110   
                  (0.128)         (0.055)         (0.084)   
age                -0.003           0.001           0.002   
                  (0.007)         (0.003)         (0.006)   
income              0.029           0.156           0.117   
                  (0.310)         (0.108)         (0.176)   
university         -0.077          -0.033          -0.101   
                  (0.129)         (0.057)         (0.098)   
_cons               0.708*          0.243           0.363   
                  (0.332)         (0.145)         (0.219)   
------------------------------------------------------------
r2_w                0.106           0.109           0.101   
r2_b                0.055           0.202           0.185   
r2_o                0.095           0.131           0.120   
N                 255.000         300.000         250.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.071           0.006           0.040   
                  (0.088)         (0.161)         (0.057)   
wp_right2           0.241          -0.379           0.070   
                  (0.406)         (0.391)         (0.251)   
c.neg#c.wp~2        0.220           0.194          -0.049   
                  (0.309)         (0.402)         (0.200)   
vid_order          -0.133***       -0.048          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.100           0.112          -0.178*  
                  (0.132)         (0.152)         (0.082)   
age                -0.011           0.010           0.001   
                  (0.023)         (0.039)         (0.007)   
income             -0.392          -0.043           0.451*  
                  (0.300)         (0.377)         (0.228)   
university         -0.254          -0.100           0.167   
                  (0.188)         (0.292)         (0.124)   
_cons               1.094           0.098          -0.090   
                  (0.684)         (0.867)         (0.304)   
------------------------------------------------------------
r2_w                0.075           0.016           0.101   
r2_b                0.154           0.163           0.205   
r2_o                0.095           0.035           0.129   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b
&gt;  r2_o N N_g)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.063          -0.060           0.082          -0.097   
                  (0.170)         (0.080)         (0.152)         (0.069)   
wp_right2           0.139           0.236           0.283           0.017   
                  (0.484)         (0.246)         (0.252)         (0.137)   
c.neg#c.wp~2       -0.004           0.208          -0.067           0.160   
                  (0.445)         (0.211)         (0.252)         (0.112)   
vid_order          -0.099**        -0.087***       -0.062*         -0.020*  
                  (0.034)         (0.021)         (0.026)         (0.009)   
female              0.073          -0.090           0.110          -0.008   
                  (0.150)         (0.102)         (0.104)         (0.048)   
age                -0.046          -0.004           0.005           0.003   
                  (0.049)         (0.002)         (0.005)         (0.002)   
income             -0.389           0.094          -0.058           0.210   
                  (0.291)         (0.160)         (0.263)         (0.146)   
university         -0.055           0.012          -0.075           0.015   
                  (0.233)         (0.098)         (0.159)         (0.048)   
_cons               1.526           0.390*         -0.066          -0.091   
                  (1.120)         (0.195)         (0.311)         (0.134)   
----------------------------------------------------------------------------
r2_w                0.052           0.108           0.042           0.023   
r2_b                0.189           0.331           0.225           0.112   
r2_o                0.075           0.144           0.073           0.044   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.101          -0.012           0.051   
                  (0.068)         (0.082)         (0.056)   
wp_right2           0.108           0.012           0.125   
                  (0.184)         (0.302)         (0.157)   
c.neg#c.wp~2        0.198           0.274           0.005   
                  (0.173)         (0.235)         (0.132)   
vid_order          -0.025          -0.077***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.094          -0.097          -0.033   
                  (0.085)         (0.110)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.425          -0.094          -0.010   
                  (0.217)         (0.220)         (0.120)   
university          0.051          -0.054           0.078   
                  (0.087)         (0.149)         (0.062)   
_cons               0.161           0.480*         -0.006   
                  (0.195)         (0.225)         (0.141)   
------------------------------------------------------------
r2_w                0.028           0.086           0.020   
r2_b                0.219           0.058           0.026   
r2_o                0.068           0.078           0.022   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.      
.           
. * Table 5 Columns 2 , 3 and 4
.  
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(56,936 real changes made, 39,228 to missing)
.   quietly xtreg p_gslmc_all neg pho_order female age income university if wp_
&gt; right2_dichox==0 &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all neg pho_order female age income university if wp_
&gt; right2_dichox==1 &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store C
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.007**         0.013***
                  (0.002)         (0.002)         (0.003)   
pho_order           0.002**         0.002**         0.002***
                  (0.001)         (0.001)         (0.000)   
female              0.010           0.013           0.012   
                  (0.010)         (0.010)         (0.007)   
age                -0.001          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.009          -0.024          -0.018   
                  (0.022)         (0.021)         (0.015)   
university         -0.002           0.014           0.006   
                  (0.011)         (0.010)         (0.007)   
wp_right2                                           0.050   
                                                  (0.037)   
c.neg#c.wp~2                                       -0.012   
                                                  (0.007)   
_cons              -0.040          -0.059*         -0.070** 
                  (0.025)         (0.024)         (0.023)   
------------------------------------------------------------
r2_w                0.003           0.003           0.003   
r2_b                0.019           0.016           0.015   
r2_o                0.004           0.003           0.003   
N                7783.000        7480.000       15263.000   
N_g               410.000         394.000         804.000   
------------------------------------------------------------
.   
. * Table 6 Column 1
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H  
.   esttab B D E , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.006           0.007          -0.003   
                  (0.017)         (0.013)         (0.016)   
wp_right2          -0.105           0.009          -0.288   
                  (0.214)         (0.220)         (0.230)   
c.neg#c.wp~2        0.011           0.015           0.037   
                  (0.042)         (0.040)         (0.044)   
pho_order           0.005*          0.006*          0.002   
                  (0.002)         (0.003)         (0.003)   
female             -0.023           0.070           0.031   
                  (0.037)         (0.061)         (0.040)   
age                -0.002           0.000          -0.001   
                  (0.004)         (0.002)         (0.002)   
income             -0.087          -0.145          -0.005   
                  (0.079)         (0.118)         (0.115)   
university          0.015           0.121          -0.051   
                  (0.037)         (0.063)         (0.041)   
_cons               0.008          -0.178           0.073   
                  (0.131)         (0.142)         (0.125)   
------------------------------------------------------------
r2_w                0.013           0.014           0.003   
r2_b                0.178           0.232           0.155   
r2_o                0.018           0.032           0.008   
N                 623.000         513.000         684.000   
N_g                33.000          27.000          36.000   
------------------------------------------------------------
.   esttab F G H , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.009           0.007           0.030*  
                  (0.027)         (0.009)         (0.015)   
wp_right2          -0.071          -0.026           0.212   
                  (0.274)         (0.145)         (0.197)   
c.neg#c.wp~2        0.030          -0.004          -0.029   
                  (0.052)         (0.026)         (0.038)   
pho_order           0.002           0.003*          0.005*  
                  (0.003)         (0.001)         (0.002)   
female              0.039          -0.067*          0.018   
                  (0.036)         (0.028)         (0.030)   
age                 0.001          -0.000           0.000   
                  (0.003)         (0.001)         (0.002)   
income              0.013           0.036          -0.046   
                  (0.095)         (0.060)         (0.074)   
university          0.012          -0.013           0.072*  
                  (0.053)         (0.028)         (0.030)   
_cons              -0.070          -0.060          -0.283** 
                  (0.174)         (0.075)         (0.106)   
------------------------------------------------------------
r2_w                0.002           0.012           0.016   
r2_b                0.056           0.192           0.267   
r2_o                0.004           0.027           0.024   
N                1045.000         665.000         969.000   
N_g                55.000          35.000          51.000   
------------------------------------------------------------
.   
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab I J K , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014           0.005           0.012   
                  (0.015)         (0.017)         (0.013)   
wp_right2           0.020           0.061           0.322   
                  (0.124)         (0.136)         (0.205)   
c.neg#c.wp~2       -0.015          -0.015          -0.041   
                  (0.023)         (0.026)         (0.037)   
pho_order           0.003*          0.001           0.001   
                  (0.001)         (0.002)         (0.002)   
female              0.020           0.026           0.004   
                  (0.022)         (0.025)         (0.039)   
age                -0.000          -0.001           0.002   
                  (0.001)         (0.002)         (0.005)   
income             -0.025          -0.029          -0.029   
                  (0.043)         (0.055)         (0.078)   
university         -0.022           0.020           0.007   
                  (0.023)         (0.029)         (0.055)   
_cons              -0.045          -0.014          -0.143   
                  (0.090)         (0.104)         (0.173)   
------------------------------------------------------------
r2_w                0.006           0.002           0.003   
r2_b                0.073           0.064           0.115   
r2_o                0.011           0.004           0.008   
N                1140.000         911.000         456.000   
N_g                60.000          48.000          24.000   
------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.037           0.008           0.027   
                  (0.019)         (0.010)         (0.026)   
wp_right2          -0.385           0.020           0.061   
                  (0.247)         (0.178)         (0.359)   
c.neg#c.wp~2        0.072          -0.012          -0.015   
                  (0.048)         (0.035)         (0.068)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.032          -0.032           0.019   
                  (0.044)         (0.026)         (0.054)   
age                 0.005          -0.002           0.014   
                  (0.011)         (0.002)         (0.018)   
income             -0.145           0.120           0.058   
                  (0.106)         (0.072)         (0.105)   
university          0.133          -0.004          -0.105   
                  (0.119)         (0.039)         (0.085)   
_cons              -0.064          -0.048          -0.282   
                  (0.266)         (0.107)         (0.423)   
------------------------------------------------------------
r2_w                0.017           0.011           0.007   
r2_b                0.212           0.124           0.095   
r2_o                0.030           0.017           0.010   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.046***        0.057**        -0.009   
                  (0.013)         (0.019)         (0.011)   
wp_right2           0.201           0.402*         -0.093   
                  (0.191)         (0.164)         (0.088)   
c.neg#c.wp~2       -0.077*         -0.072*          0.019   
                  (0.035)         (0.032)         (0.017)   
pho_order           0.001          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.003          -0.014           0.016   
                  (0.043)         (0.032)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.001          -0.061          -0.037   
                  (0.068)         (0.080)         (0.043)   
university         -0.013          -0.036           0.001   
                  (0.041)         (0.048)         (0.014)   
_cons              -0.133          -0.170           0.056   
                  (0.102)         (0.127)         (0.064)   
------------------------------------------------------------
r2_w                0.025           0.018           0.004   
r2_b                0.163           0.136           0.108   
r2_o                0.033           0.022           0.006   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009           0.009           0.016   
                  (0.011)         (0.012)         (0.011)   
wp_right2          -0.104           0.046           0.100   
                  (0.152)         (0.178)         (0.142)   
c.neg#c.wp~2        0.015          -0.018          -0.019   
                  (0.029)         (0.034)         (0.028)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.059           0.053           0.005   
                  (0.032)         (0.030)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income             -0.012          -0.078           0.045   
                  (0.082)         (0.061)         (0.045)   
university          0.022          -0.053           0.021   
                  (0.033)         (0.041)         (0.023)   
_cons              -0.154           0.010          -0.090   
                  (0.090)         (0.087)         (0.072)   
------------------------------------------------------------
r2_w                0.009           0.002           0.002   
r2_b                0.193           0.152           0.033   
r2_o                0.020           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.         
. * Table A3 Row 2
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(56,936 real changes made, 17,708 to missing)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A    
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store B 
.   esttab A B , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2_
&gt; o N N_g)

--------------------------------------------
                      (1)             (2)   
                    gslmc           gslmc   
                     b/se            b/se   
--------------------------------------------
neg                 0.017           0.023   
                  (0.022)         (0.032)   
wp_right2           0.063          -0.108   
                  (0.052)         (0.077)   
c.neg#c.wp~2        0.045          -0.078   
                  (0.048)         (0.068)   
vid_order          -0.074***       -0.078***
                  (0.005)         (0.008)   
female             -0.027          -0.011   
                  (0.023)         (0.034)   
age                 0.001           0.001   
                  (0.001)         (0.001)   
income              0.016          -0.001   
                  (0.049)         (0.072)   
university         -0.021          -0.054   
                  (0.025)         (0.036)   
_cons               0.215***        0.327***
                  (0.055)         (0.083)   
--------------------------------------------
r2_w                0.050           0.079   
r2_b                0.037           0.022   
r2_o                0.046           0.048   
N                4665.000        1866.000   
N_g               933.000         933.000   
--------------------------------------------
.    
.    
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b
&gt;  r2_o N N_g)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.017          -0.036          -0.112          -0.078   
                  (0.022)         (0.139)         (0.101)         (0.061)   
wp_right2           0.063          -0.275          -0.112          -0.268   
                  (0.052)         (0.325)         (0.571)         (0.203)   
c.neg#c.wp~2        0.045           0.140           0.731*          0.134   
                  (0.048)         (0.338)         (0.341)         (0.188)   
vid_order          -0.074***       -0.071*         -0.122***       -0.042*  
                  (0.005)         (0.030)         (0.030)         (0.019)   
female             -0.027          -0.083           0.188          -0.013   
                  (0.023)         (0.122)         (0.249)         (0.101)   
age                 0.001           0.013           0.025          -0.002   
                  (0.001)         (0.012)         (0.025)         (0.003)   
income              0.016           0.021          -0.201           0.050   
                  (0.049)         (0.281)         (0.443)         (0.197)   
university         -0.021          -0.016          -0.167          -0.061   
                  (0.025)         (0.129)         (0.336)         (0.105)   
_cons               0.215***        0.097          -0.176           0.326   
                  (0.055)         (0.349)         (0.779)         (0.228)   
----------------------------------------------------------------------------
r2_w                0.050           0.048           0.152           0.059   
r2_b                0.037           0.121           0.085           0.077   
r2_o                0.046           0.057           0.129           0.063   
N                4665.000         175.000         160.000         135.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.104          -0.086          -0.082   
                  (0.120)         (0.186)         (0.082)   
wp_right2           0.445          -0.112           0.067   
                  (0.481)         (0.383)         (0.252)   
c.neg#c.wp~2       -0.110           0.224           0.342   
                  (0.329)         (0.361)         (0.239)   
vid_order          -0.108***       -0.111***       -0.041*  
                  (0.029)         (0.023)         (0.019)   
female              0.170           0.006          -0.008   
                  (0.172)         (0.105)         (0.086)   
age                 0.005          -0.011           0.001   
                  (0.007)         (0.010)         (0.003)   
income              0.100           0.429           0.252   
                  (0.497)         (0.257)         (0.184)   
university          0.229          -0.133          -0.009   
                  (0.176)         (0.153)         (0.085)   
_cons              -0.341           0.668          -0.044   
                  (0.426)         (0.355)         (0.200)   
------------------------------------------------------------
r2_w                0.099           0.094           0.042   
r2_b                0.129           0.130           0.163   
r2_o                0.108           0.099           0.057   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.068           0.153           0.109   
                  (0.125)         (0.097)         (0.110)   
wp_right2          -0.090          -0.077          -0.236   
                  (0.394)         (0.161)         (0.209)   
c.neg#c.wp~2        0.077          -0.205          -0.176   
                  (0.311)         (0.149)         (0.172)   
vid_order          -0.119***       -0.067***       -0.087***
                  (0.026)         (0.012)         (0.018)   
female             -0.106          -0.124*         -0.110   
                  (0.128)         (0.055)         (0.084)   
age                -0.003           0.001           0.002   
                  (0.007)         (0.003)         (0.006)   
income              0.029           0.156           0.117   
                  (0.310)         (0.108)         (0.176)   
university         -0.077          -0.033          -0.101   
                  (0.129)         (0.057)         (0.098)   
_cons               0.708*          0.243           0.363   
                  (0.332)         (0.145)         (0.219)   
------------------------------------------------------------
r2_w                0.106           0.109           0.101   
r2_b                0.055           0.202           0.185   
r2_o                0.095           0.131           0.120   
N                 255.000         300.000         250.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.071           0.006           0.040   
                  (0.088)         (0.161)         (0.057)   
wp_right2           0.241          -0.379           0.070   
                  (0.406)         (0.391)         (0.251)   
c.neg#c.wp~2        0.220           0.194          -0.049   
                  (0.309)         (0.402)         (0.200)   
vid_order          -0.133***       -0.048          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.100           0.112          -0.178*  
                  (0.132)         (0.152)         (0.082)   
age                -0.011           0.010           0.001   
                  (0.023)         (0.039)         (0.007)   
income             -0.392          -0.043           0.451*  
                  (0.300)         (0.377)         (0.228)   
university         -0.254          -0.100           0.167   
                  (0.188)         (0.292)         (0.124)   
_cons               1.094           0.098          -0.090   
                  (0.684)         (0.867)         (0.304)   
------------------------------------------------------------
r2_w                0.075           0.016           0.101   
r2_b                0.154           0.163           0.205   
r2_o                0.095           0.035           0.129   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.063          -0.060           0.082          -0.097   
                  (0.170)         (0.080)         (0.152)         (0.069)   
wp_right2           0.139           0.236           0.283           0.017   
                  (0.484)         (0.246)         (0.252)         (0.137)   
c.neg#c.wp~2       -0.004           0.208          -0.067           0.160   
                  (0.445)         (0.211)         (0.252)         (0.112)   
vid_order          -0.099**        -0.087***       -0.062*         -0.020*  
                  (0.034)         (0.021)         (0.026)         (0.009)   
female              0.073          -0.090           0.110          -0.008   
                  (0.150)         (0.102)         (0.104)         (0.048)   
age                -0.046          -0.004           0.005           0.003   
                  (0.049)         (0.002)         (0.005)         (0.002)   
income             -0.389           0.094          -0.058           0.210   
                  (0.291)         (0.160)         (0.263)         (0.146)   
university         -0.055           0.012          -0.075           0.015   
                  (0.233)         (0.098)         (0.159)         (0.048)   
_cons               1.526           0.390*         -0.066          -0.091   
                  (1.120)         (0.195)         (0.311)         (0.134)   
----------------------------------------------------------------------------
r2_w                0.052           0.108           0.042           0.023   
r2_b                0.189           0.331           0.225           0.112   
r2_o                0.075           0.144           0.073           0.044   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.101          -0.012           0.051   
                  (0.068)         (0.082)         (0.056)   
wp_right2           0.108           0.012           0.125   
                  (0.184)         (0.302)         (0.157)   
c.neg#c.wp~2        0.198           0.274           0.005   
                  (0.173)         (0.235)         (0.132)   
vid_order          -0.025          -0.077***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.094          -0.097          -0.033   
                  (0.085)         (0.110)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.425          -0.094          -0.010   
                  (0.217)         (0.220)         (0.120)   
university          0.051          -0.054           0.078   
                  (0.087)         (0.149)         (0.062)   
_cons               0.161           0.480*         -0.006   
                  (0.195)         (0.225)         (0.141)   
------------------------------------------------------------
r2_w                0.028           0.086           0.020   
r2_b                0.219           0.058           0.026   
r2_o                0.068           0.078           0.022   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.023          -0.042           0.026          -0.134   
                  (0.032)         (0.159)         (0.140)         (0.091)   
wp_right2          -0.108          -1.279*         -0.197          -0.434   
                  (0.077)         (0.604)         (0.776)         (0.296)   
c.neg#c.wp~2       -0.078           0.080           0.384           0.335   
                  (0.068)         (0.393)         (0.517)         (0.267)   
vid_order          -0.078***       -0.063          -0.065          -0.021   
                  (0.008)         (0.048)         (0.055)         (0.031)   
female             -0.011          -0.378           0.647          -0.244   
                  (0.034)         (0.224)         (0.342)         (0.148)   
age                 0.001          -0.082***        0.030           0.000   
                  (0.001)         (0.021)         (0.035)         (0.005)   
income             -0.001           1.338**        -0.133          -0.107   
                  (0.072)         (0.514)         (0.608)         (0.302)   
university         -0.054           0.166          -0.505           0.092   
                  (0.036)         (0.236)         (0.461)         (0.159)   
_cons               0.327***        2.241***       -0.580           0.366   
                  (0.083)         (0.635)         (1.076)         (0.294)   
----------------------------------------------------------------------------
r2_w                0.079           0.084           0.141           0.136   
r2_b                0.022           0.401           0.206           0.222   
r2_o                0.048           0.281           0.183           0.181   
N                1866.000          70.000          64.000          54.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.080           0.010           0.040   
                  (0.146)         (0.156)         (0.039)   
wp_right2          -0.047          -0.172          -0.104   
                  (0.518)         (0.690)         (0.248)   
c.neg#c.wp~2       -0.405          -0.361          -0.038   
                  (0.390)         (0.305)         (0.115)   
vid_order          -0.111**        -0.057          -0.024   
                  (0.041)         (0.033)         (0.018)   
female              0.079           0.095          -0.050   
                  (0.181)         (0.190)         (0.086)   
age                 0.001           0.022           0.002   
                  (0.008)         (0.018)         (0.003)   
income             -0.199           0.300           0.240   
                  (0.523)         (0.463)         (0.183)   
university         -0.019          -0.177           0.023   
                  (0.185)         (0.278)         (0.085)   
_cons               0.424          -0.290          -0.093   
                  (0.442)         (0.644)         (0.199)   
------------------------------------------------------------
r2_w                0.156           0.271           0.123   
r2_b                0.105           0.078           0.078   
r2_o                0.129           0.156           0.099   
N                  72.000         112.000          70.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store M
.   esttab H I J , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.153           0.026          -0.001   
                  (0.195)         (0.103)         (0.421)   
wp_right2          -1.049*         -0.082           0.116   
                  (0.450)         (0.328)         (0.574)   
c.neg#c.wp~2       -0.007          -0.027          -0.372   
                  (0.488)         (0.158)         (0.658)   
vid_order          -0.073          -0.057**        -0.109*  
                  (0.038)         (0.022)         (0.048)   
female             -0.368*         -0.020          -0.005   
                  (0.148)         (0.114)         (0.210)   
age                 0.002          -0.000           0.007   
                  (0.008)         (0.006)         (0.014)   
income             -0.046          -0.153          -0.110   
                  (0.355)         (0.224)         (0.440)   
university          0.040          -0.005           0.074   
                  (0.147)         (0.119)         (0.245)   
_cons               0.950*          0.359           0.125   
                  (0.395)         (0.298)         (0.617)   
------------------------------------------------------------
r2_w                0.103           0.098           0.184   
r2_b                0.268           0.031           0.012   
r2_o                0.187           0.055           0.092   
N                 102.000         120.000         100.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.129          -0.075          -0.149   
                  (0.133)         (0.235)         (0.283)   
wp_right2           0.192          -0.321          -1.040   
                  (0.466)         (0.514)         (1.034)   
c.neg#c.wp~2        0.391           0.441           0.808   
                  (0.474)         (0.585)         (1.003)   
vid_order          -0.147***       -0.053          -0.040   
                  (0.037)         (0.051)         (0.022)   
female             -0.005           0.150           0.091   
                  (0.154)         (0.198)         (0.115)   
age                -0.004          -0.018          -0.012   
                  (0.027)         (0.052)         (0.010)   
income             -0.159          -0.785          -0.572   
                  (0.348)         (0.491)         (0.320)   
university         -0.432*         -0.150          -0.148   
                  (0.218)         (0.387)         (0.173)   
_cons               1.067           0.943           1.096*  
                  (0.795)         (1.262)         (0.508)   
------------------------------------------------------------
r2_w                0.313           0.019           0.135   
r2_b                0.022           0.222           0.138   
r2_o                0.151           0.085           0.128   
N                 142.000          64.000          74.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==1 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.209          -0.123           0.414          -0.036   
                  (0.333)         (0.094)         (0.236)         (0.112)   
wp_right2           0.684          -0.572          -0.455           0.015   
                  (0.892)         (0.485)         (0.475)         (0.296)   
c.neg#c.wp~2       -0.234           0.279          -0.423           0.038   
                  (0.890)         (0.247)         (0.386)         (0.179)   
vid_order          -0.210**        -0.011          -0.071          -0.024   
                  (0.065)         (0.033)         (0.046)         (0.023)   
female              0.149          -0.176          -0.031          -0.056   
                  (0.240)         (0.201)         (0.195)         (0.097)   
age                -0.094          -0.008           0.005           0.000   
                  (0.077)         (0.005)         (0.010)         (0.005)   
income             -0.066           0.141          -0.139          -0.328   
                  (0.465)         (0.319)         (0.496)         (0.297)   
university          0.554          -0.127           0.351          -0.037   
                  (0.373)         (0.193)         (0.301)         (0.098)   
_cons               1.898           0.894*          0.031           0.253   
                  (1.785)         (0.403)         (0.551)         (0.277)   
----------------------------------------------------------------------------
r2_w                0.345           0.059           0.187           0.067   
r2_b                0.189           0.240           0.218           0.026   
r2_o                0.273           0.171           0.198           0.036   
N                  72.000          64.000          64.000          96.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.119           0.040           0.021   
                  (0.171)         (0.147)         (0.096)   
wp_right2           0.102          -0.522           0.280   
                  (0.335)         (0.493)         (0.223)   
c.neg#c.wp~2       -0.154          -0.206           0.064   
                  (0.434)         (0.418)         (0.228)   
vid_order          -0.100**        -0.089*         -0.089***
                  (0.033)         (0.043)         (0.020)   
female              0.037           0.025           0.048   
                  (0.154)         (0.180)         (0.086)   
age                -0.003           0.002           0.001   
                  (0.006)         (0.007)         (0.004)   
income              0.644          -0.050          -0.095   
                  (0.397)         (0.363)         (0.169)   
university         -0.118          -0.185          -0.016   
                  (0.158)         (0.245)         (0.086)   
_cons               0.115           0.472           0.199   
                  (0.351)         (0.412)         (0.199)   
------------------------------------------------------------
r2_w                0.149           0.055           0.073   
r2_b                0.339           0.197           0.052   
r2_o                0.217           0.069           0.061   
N                  62.000          96.000         368.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.  
. * Table A4 Row 2 
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(56,936 real changes made, 39,228 to missing)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_negative==0) , re 
.   estimates store A  
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_negative==0) , re 
.   estimates store B  
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_negative==0) , re 
.   estimates store C
.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.014***        0.010** 
                  (0.003)         (0.004)         (0.004)   
wp_right2           0.050           0.056           0.042   
                  (0.037)         (0.038)         (0.038)   
c.neg#c.wp~2       -0.012          -0.014          -0.008   
                  (0.007)         (0.009)         (0.008)   
pho_order           0.002***        0.003***        0.002***
                  (0.000)         (0.001)         (0.001)   
female              0.012           0.005           0.008   
                  (0.007)         (0.008)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.018          -0.007          -0.020   
                  (0.015)         (0.017)         (0.017)   
university          0.006           0.008           0.004   
                  (0.007)         (0.008)         (0.008)   
_cons              -0.070**        -0.090***       -0.071** 
                  (0.023)         (0.024)         (0.025)   
------------------------------------------------------------
r2_w                0.003           0.004           0.003   
r2_b                0.015           0.014           0.007   
r2_o                0.003           0.004           0.003   
N               15263.000       12049.000       11245.000   
N_g               804.000         804.000         804.000   
------------------------------------------------------------
.    
.    
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_negative==0) , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_
&gt; negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.007   
                  (0.003)         (0.017)         (0.013)   
wp_right2           0.050          -0.105           0.009   
                  (0.037)         (0.214)         (0.220)   
c.neg#c.wp~2       -0.012           0.011           0.015   
                  (0.007)         (0.042)         (0.040)   
pho_order           0.002***        0.005*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.023           0.070   
                  (0.007)         (0.037)         (0.061)   
age                -0.000          -0.002           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.018          -0.087          -0.145   
                  (0.015)         (0.079)         (0.118)   
university          0.006           0.015           0.121   
                  (0.007)         (0.037)         (0.063)   
_cons              -0.070**         0.008          -0.178   
                  (0.023)         (0.131)         (0.142)   
------------------------------------------------------------
r2_w                0.003           0.013           0.014   
r2_b                0.015           0.178           0.232   
r2_o                0.003           0.018           0.032   
N               15263.000         623.000         513.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003          -0.009           0.007   
                  (0.016)         (0.027)         (0.009)   
wp_right2          -0.288          -0.071          -0.026   
                  (0.230)         (0.274)         (0.145)   
c.neg#c.wp~2        0.037           0.030          -0.004   
                  (0.044)         (0.052)         (0.026)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.031           0.039          -0.067*  
                  (0.040)         (0.036)         (0.028)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income             -0.005           0.013           0.036   
                  (0.115)         (0.095)         (0.060)   
university         -0.051           0.012          -0.013   
                  (0.041)         (0.053)         (0.028)   
_cons               0.073          -0.070          -0.060   
                  (0.125)         (0.174)         (0.075)   
------------------------------------------------------------
r2_w                0.003           0.002           0.012   
r2_b                0.155           0.056           0.192   
r2_o                0.008           0.004           0.027   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_
&gt; negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_
&gt; negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.030*          0.014           0.005           0.012   
                  (0.015)         (0.015)         (0.017)         (0.013)   
wp_right2           0.212           0.020           0.061           0.322   
                  (0.197)         (0.124)         (0.136)         (0.205)   
c.neg#c.wp~2       -0.029          -0.015          -0.015          -0.041   
                  (0.038)         (0.023)         (0.026)         (0.037)   
pho_order           0.005*          0.003*          0.001           0.001   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.018           0.020           0.026           0.004   
                  (0.030)         (0.022)         (0.025)         (0.039)   
age                 0.000          -0.000          -0.001           0.002   
                  (0.002)         (0.001)         (0.002)         (0.005)   
income             -0.046          -0.025          -0.029          -0.029   
                  (0.074)         (0.043)         (0.055)         (0.078)   
university          0.072*         -0.022           0.020           0.007   
                  (0.030)         (0.023)         (0.029)         (0.055)   
_cons              -0.283**        -0.045          -0.014          -0.143   
                  (0.106)         (0.090)         (0.104)         (0.173)   
----------------------------------------------------------------------------
r2_w                0.016           0.006           0.002           0.003   
r2_b                0.267           0.073           0.064           0.115   
r2_o                0.024           0.011           0.004           0.008   
N                 969.000        1140.000         911.000         456.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.037           0.008           0.027   
                  (0.019)         (0.010)         (0.026)   
wp_right2          -0.385           0.020           0.061   
                  (0.247)         (0.178)         (0.359)   
c.neg#c.wp~2        0.072          -0.012          -0.015   
                  (0.048)         (0.035)         (0.068)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.032          -0.032           0.019   
                  (0.044)         (0.026)         (0.054)   
age                 0.005          -0.002           0.014   
                  (0.011)         (0.002)         (0.018)   
income             -0.145           0.120           0.058   
                  (0.106)         (0.072)         (0.105)   
university          0.133          -0.004          -0.105   
                  (0.119)         (0.039)         (0.085)   
_cons              -0.064          -0.048          -0.282   
                  (0.266)         (0.107)         (0.423)   
------------------------------------------------------------
r2_w                0.017           0.011           0.007   
r2_b                0.212           0.124           0.095   
r2_o                0.030           0.017           0.010   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (p_negative==1 | p_ne
&gt; gative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.046***        0.057**        -0.009   
                  (0.013)         (0.019)         (0.011)   
wp_right2           0.201           0.402*         -0.093   
                  (0.191)         (0.164)         (0.088)   
c.neg#c.wp~2       -0.077*         -0.072*          0.019   
                  (0.035)         (0.032)         (0.017)   
pho_order           0.001          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.003          -0.014           0.016   
                  (0.043)         (0.032)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.001          -0.061          -0.037   
                  (0.068)         (0.080)         (0.043)   
university         -0.013          -0.036           0.001   
                  (0.041)         (0.048)         (0.014)   
_cons              -0.133          -0.170           0.056   
                  (0.102)         (0.127)         (0.064)   
------------------------------------------------------------
r2_w                0.025           0.018           0.004   
r2_b                0.163           0.136           0.108   
r2_o                0.033           0.022           0.006   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009           0.009           0.016   
                  (0.011)         (0.012)         (0.011)   
wp_right2          -0.104           0.046           0.100   
                  (0.152)         (0.178)         (0.142)   
c.neg#c.wp~2        0.015          -0.018          -0.019   
                  (0.029)         (0.034)         (0.028)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.059           0.053           0.005   
                  (0.032)         (0.030)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income             -0.012          -0.078           0.045   
                  (0.082)         (0.061)         (0.045)   
university          0.022          -0.053           0.021   
                  (0.033)         (0.041)         (0.023)   
_cons              -0.154           0.010          -0.090   
                  (0.090)         (0.087)         (0.072)   
------------------------------------------------------------
r2_w                0.009           0.002           0.002   
r2_b                0.193           0.152           0.033   
r2_o                0.020           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.              
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_negative==0) , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p
&gt; _negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***       -0.024           0.011   
                  (0.004)         (0.021)         (0.016)   
wp_right2           0.056          -0.334           0.037   
                  (0.038)         (0.232)         (0.242)   
c.neg#c.wp~2       -0.014           0.097           0.014   
                  (0.009)         (0.051)         (0.048)   
pho_order           0.003***        0.007**         0.007*  
                  (0.001)         (0.003)         (0.003)   
female              0.005          -0.004           0.102   
                  (0.008)         (0.042)         (0.074)   
age                -0.000           0.001           0.000   
                  (0.000)         (0.004)         (0.003)   
income             -0.007          -0.119          -0.208   
                  (0.017)         (0.092)         (0.144)   
university          0.008           0.037           0.153*  
                  (0.008)         (0.043)         (0.077)   
_cons              -0.090***       -0.036          -0.224   
                  (0.024)         (0.148)         (0.169)   
------------------------------------------------------------
r2_w                0.004           0.028           0.022   
r2_b                0.014           0.135           0.250   
r2_o                0.004           0.031           0.051   
N               12049.000         492.000         405.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.006           0.006   
                  (0.019)         (0.030)         (0.009)   
wp_right2          -0.277           0.065           0.013   
                  (0.240)         (0.269)         (0.140)   
c.neg#c.wp~2        0.033          -0.002          -0.005   
                  (0.052)         (0.058)         (0.027)   
pho_order           0.003           0.002           0.002   
                  (0.003)         (0.003)         (0.001)   
female              0.023           0.018          -0.047   
                  (0.045)         (0.038)         (0.031)   
age                -0.001          -0.000           0.000   
                  (0.002)         (0.004)         (0.001)   
income              0.003           0.066           0.008   
                  (0.129)         (0.099)         (0.066)   
university         -0.048          -0.031           0.001   
                  (0.046)         (0.055)         (0.031)   
_cons               0.065          -0.085          -0.070   
                  (0.136)         (0.175)         (0.077)   
------------------------------------------------------------
r2_w                0.004           0.001           0.005   
r2_b                0.136           0.025           0.106   
r2_o                0.009           0.002           0.017   
N                 540.000         825.000         525.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p
&gt; _negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p
&gt; _negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.023           0.019           0.006           0.002   
                  (0.018)         (0.019)         (0.021)         (0.016)   
wp_right2           0.154           0.052           0.087           0.254   
                  (0.206)         (0.139)         (0.148)         (0.237)   
c.neg#c.wp~2       -0.008          -0.027          -0.020          -0.024   
                  (0.045)         (0.029)         (0.032)         (0.046)   
pho_order           0.007**         0.004**         0.002           0.000   
                  (0.002)         (0.001)         (0.002)         (0.003)   
female              0.032           0.018           0.003           0.021   
                  (0.034)         (0.028)         (0.029)         (0.052)   
age                 0.000          -0.000          -0.001           0.003   
                  (0.002)         (0.001)         (0.002)         (0.007)   
income             -0.095          -0.007           0.010          -0.082   
                  (0.082)         (0.054)         (0.063)         (0.105)   
university          0.069*         -0.023           0.017          -0.005   
                  (0.034)         (0.029)         (0.034)         (0.074)   
_cons              -0.260*         -0.077          -0.051          -0.095   
                  (0.114)         (0.103)         (0.116)         (0.225)   
----------------------------------------------------------------------------
r2_w                0.020           0.010           0.004           0.002   
r2_b                0.362           0.063           0.007           0.166   
r2_o                0.032           0.015           0.005           0.015   
N                 765.000         900.000         720.000         360.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.050*          0.005           0.012   
                  (0.024)         (0.012)         (0.028)   
wp_right2          -0.389          -0.005          -0.051   
                  (0.265)         (0.189)         (0.340)   
c.neg#c.wp~2        0.078          -0.001           0.007   
                  (0.059)         (0.042)         (0.073)   
pho_order           0.008**         0.004*         -0.002   
                  (0.003)         (0.002)         (0.003)   
female             -0.076          -0.045          -0.016   
                  (0.050)         (0.029)         (0.055)   
age                 0.005          -0.003           0.007   
                  (0.013)         (0.002)         (0.018)   
income             -0.079           0.066           0.006   
                  (0.121)         (0.081)         (0.106)   
university          0.140          -0.013           0.016   
                  (0.136)         (0.044)         (0.085)   
_cons              -0.063           0.014          -0.156   
                  (0.299)         (0.118)         (0.424)   
------------------------------------------------------------
r2_w                0.026           0.013           0.004   
r2_b                0.229           0.082           0.032   
r2_o                0.042           0.017           0.004   
N                 465.000         555.000         540.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (threatening==1 | p_n
&gt; egative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.062***        0.080***        0.000   
                  (0.016)         (0.022)         (0.013)   
wp_right2           0.262           0.497**        -0.057   
                  (0.200)         (0.167)         (0.094)   
c.neg#c.wp~2       -0.101*         -0.112**         0.004   
                  (0.042)         (0.037)         (0.021)   
pho_order           0.002           0.002           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.006          -0.034           0.031   
                  (0.045)         (0.034)         (0.016)   
age                -0.000          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.016           0.056          -0.050   
                  (0.071)         (0.087)         (0.050)   
university          0.003          -0.050          -0.001   
                  (0.043)         (0.053)         (0.016)   
_cons              -0.210          -0.279*          0.025   
                  (0.107)         (0.134)         (0.070)   
------------------------------------------------------------
r2_w                0.040           0.029           0.003   
r2_b                0.127           0.221           0.229   
r2_o                0.046           0.036           0.011   
N                 480.000         480.000         720.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.024           0.003           0.018   
                  (0.014)         (0.014)         (0.013)   
wp_right2          -0.062          -0.024           0.092   
                  (0.164)         (0.187)         (0.149)   
c.neg#c.wp~2       -0.020           0.016          -0.012   
                  (0.035)         (0.040)         (0.033)   
pho_order           0.001           0.002           0.001   
                  (0.002)         (0.002)         (0.002)   
female              0.042           0.029          -0.005   
                  (0.040)         (0.036)         (0.024)   
age                 0.003          -0.001          -0.002*  
                  (0.002)         (0.001)         (0.001)   
income              0.106          -0.114           0.070   
                  (0.103)         (0.071)         (0.050)   
university         -0.016          -0.042           0.035   
                  (0.041)         (0.048)         (0.025)   
_cons              -0.284**         0.064          -0.109   
                  (0.104)         (0.095)         (0.077)   
------------------------------------------------------------
r2_w                0.013           0.003           0.003   
r2_b                0.248           0.111           0.079   
r2_o                0.033           0.011           0.007   
N                 462.000         715.000        2085.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.              
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_negative==0) , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_
&gt; negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010**         0.022           0.003   
                  (0.004)         (0.019)         (0.015)   
wp_right2           0.042          -0.018           0.044   
                  (0.038)         (0.213)         (0.207)   
c.neg#c.wp~2       -0.008          -0.040           0.007   
                  (0.008)         (0.047)         (0.045)   
pho_order           0.002***        0.008**         0.006*  
                  (0.001)         (0.003)         (0.003)   
female              0.008          -0.020           0.073   
                  (0.008)         (0.041)         (0.053)   
age                -0.000          -0.005           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.020          -0.027          -0.052   
                  (0.017)         (0.088)         (0.104)   
university          0.004          -0.012           0.114*  
                  (0.008)         (0.041)         (0.055)   
_cons              -0.071**        -0.008          -0.221   
                  (0.025)         (0.141)         (0.132)   
------------------------------------------------------------
r2_w                0.003           0.021           0.011   
r2_b                0.007           0.230           0.245   
r2_o                0.003           0.035           0.029   
N               11245.000         459.000         378.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.001          -0.022           0.007   
                  (0.018)         (0.031)         (0.011)   
wp_right2          -0.327          -0.133          -0.026   
                  (0.235)         (0.282)         (0.159)   
c.neg#c.wp~2        0.037           0.050          -0.003   
                  (0.050)         (0.060)         (0.031)   
pho_order           0.003           0.002           0.006***
                  (0.003)         (0.003)         (0.002)   
female              0.049           0.020          -0.061   
                  (0.047)         (0.043)         (0.035)   
age                -0.001          -0.000          -0.000   
                  (0.002)         (0.004)         (0.001)   
income              0.021          -0.038           0.066   
                  (0.136)         (0.112)         (0.076)   
university         -0.068           0.059          -0.008   
                  (0.048)         (0.062)         (0.035)   
_cons               0.046          -0.019          -0.119   
                  (0.139)         (0.188)         (0.089)   
------------------------------------------------------------
r2_w                0.007           0.002           0.027   
r2_b                0.135           0.046           0.150   
r2_o                0.016           0.005           0.042   
N                 504.000         770.000         490.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_
&gt; negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_
&gt; negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.030           0.010          -0.006           0.014   
                  (0.017)         (0.018)         (0.020)         (0.016)   
wp_right2           0.224           0.003           0.022           0.397   
                  (0.196)         (0.125)         (0.140)         (0.233)   
c.neg#c.wp~2       -0.041          -0.007           0.003          -0.038   
                  (0.042)         (0.027)         (0.030)         (0.044)   
pho_order           0.005*          0.002           0.001           0.003   
                  (0.002)         (0.001)         (0.002)         (0.003)   
female             -0.015           0.022           0.041           0.014   
                  (0.034)         (0.023)         (0.029)         (0.055)   
age                 0.002          -0.001          -0.002           0.006   
                  (0.002)         (0.001)         (0.002)         (0.007)   
income             -0.034          -0.030          -0.054           0.087   
                  (0.082)         (0.045)         (0.063)         (0.110)   
university          0.058          -0.008           0.013          -0.017   
                  (0.034)         (0.024)         (0.033)         (0.077)   
_cons              -0.298**        -0.015           0.041          -0.334   
                  (0.111)         (0.092)         (0.111)         (0.234)   
----------------------------------------------------------------------------
r2_w                0.014           0.004           0.001           0.008   
r2_b                0.172           0.046           0.130           0.123   
r2_o                0.022           0.008           0.007           0.018   
N                 714.000         840.000         671.000         336.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.031           0.008           0.043   
                  (0.024)         (0.011)         (0.032)   
wp_right2          -0.394           0.031           0.072   
                  (0.265)         (0.168)         (0.390)   
c.neg#c.wp~2        0.087          -0.021          -0.044   
                  (0.059)         (0.037)         (0.084)   
pho_order           0.009**         0.005**        -0.005   
                  (0.003)         (0.002)         (0.004)   
female             -0.058          -0.040          -0.026   
                  (0.053)         (0.027)         (0.066)   
age                 0.023          -0.003          -0.005   
                  (0.013)         (0.002)         (0.021)   
income             -0.111           0.110           0.187   
                  (0.126)         (0.076)         (0.128)   
university          0.099           0.015          -0.185   
                  (0.142)         (0.041)         (0.103)   
_cons              -0.424          -0.048           0.162   
                  (0.313)         (0.108)         (0.510)   
------------------------------------------------------------
r2_w                0.019           0.020           0.013   
r2_b                0.289           0.133           0.183   
r2_o                0.041           0.027           0.025   
N                 434.000         518.000         504.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (disgusting==1 | p_ne
&gt; gative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.021           0.036          -0.019   
                  (0.014)         (0.021)         (0.012)   
wp_right2           0.078           0.310          -0.120   
                  (0.183)         (0.160)         (0.088)   
c.neg#c.wp~2       -0.031          -0.042           0.033   
                  (0.038)         (0.035)         (0.019)   
pho_order           0.002          -0.002           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.015          -0.029           0.005   
                  (0.045)         (0.035)         (0.016)   
age                 0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.052          -0.141          -0.035   
                  (0.071)         (0.090)         (0.049)   
university         -0.004          -0.060          -0.002   
                  (0.043)         (0.054)         (0.016)   
_cons              -0.121          -0.036           0.089   
                  (0.103)         (0.131)         (0.066)   
------------------------------------------------------------
r2_w                0.008           0.010           0.005   
r2_b                0.058           0.216           0.030   
r2_o                0.012           0.026           0.006   
N                 448.000         448.000         672.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.010           0.013           0.016   
                  (0.012)         (0.015)         (0.013)   
wp_right2          -0.190           0.095           0.084   
                  (0.147)         (0.199)         (0.147)   
c.neg#c.wp~2        0.049          -0.038          -0.018   
                  (0.031)         (0.044)         (0.032)   
pho_order          -0.000           0.003           0.001   
                  (0.002)         (0.002)         (0.002)   
female              0.026           0.067           0.013   
                  (0.038)         (0.037)         (0.025)   
age                 0.002          -0.001           0.000   
                  (0.001)         (0.001)         (0.001)   
income             -0.048          -0.079           0.066   
                  (0.096)         (0.075)         (0.052)   
university          0.033          -0.056           0.015   
                  (0.038)         (0.051)         (0.026)   
_cons              -0.108          -0.021          -0.150   
                  (0.096)         (0.102)         (0.078)   
------------------------------------------------------------
r2_w                0.008           0.003           0.002   
r2_b                0.166           0.157           0.015   
r2_o                0.021           0.013           0.003   
N                 432.000         667.000        1946.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                                                  
.                                  
. * Table A5
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negative
(56,936 real changes made, 17,708 to missing)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11&quot; | v_negative==0
&gt; ) , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 11&quot; | v_negative==0) , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 11&quot; | v_negative==0) , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.116           0.047          -0.117          -0.093   
                  (0.065)         (0.330)         (0.350)         (0.186)   
wp_right2           0.019          -0.432          -0.458          -0.335   
                  (0.070)         (0.437)         (0.780)         (0.310)   
c.neg#c.wp~2       -0.072           0.385           1.296           0.158   
                  (0.146)         (0.858)         (1.162)         (0.544)   
vid_order          -0.076***       -0.035          -0.100*         -0.045   
                  (0.007)         (0.036)         (0.041)         (0.024)   
female             -0.022          -0.013           0.201           0.084   
                  (0.029)         (0.148)         (0.326)         (0.145)   
age                 0.002           0.006           0.041          -0.005   
                  (0.001)         (0.015)         (0.033)         (0.005)   
income             -0.035           0.060          -0.073          -0.049   
                  (0.060)         (0.334)         (0.578)         (0.284)   
university          0.008          -0.016          -0.139          -0.087   
                  (0.030)         (0.155)         (0.447)         (0.147)   
_cons               0.177*          0.104          -0.714           0.530   
                  (0.070)         (0.459)         (1.039)         (0.324)   
----------------------------------------------------------------------------
r2_w                0.054           0.049           0.121           0.058   
r2_b                0.035           0.026           0.147           0.100   
r2_o                0.048           0.039           0.140           0.078   
N                2872.000         114.000          95.000          83.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.453           0.043          -0.227   
                  (0.316)         (0.594)         (0.248)   
wp_right2           0.695          -0.186          -0.074   
                  (0.513)         (0.569)         (0.357)   
c.neg#c.wp~2       -0.454          -0.060           1.006   
                  (0.820)         (1.130)         (0.738)   
vid_order          -0.064          -0.121***       -0.051*  
                  (0.036)         (0.031)         (0.025)   
female              0.008          -0.098           0.036   
                  (0.161)         (0.145)         (0.113)   
age                 0.007          -0.013           0.002   
                  (0.007)         (0.015)         (0.004)   
income              0.144           0.468           0.279   
                  (0.473)         (0.351)         (0.256)   
university          0.317          -0.193           0.052   
                  (0.167)         (0.217)         (0.110)   
_cons              -0.728           0.879          -0.110   
                  (0.442)         (0.520)         (0.270)   
------------------------------------------------------------
r2_w                0.090           0.086           0.033   
r2_b                0.153           0.155           0.270   
r2_o                0.130           0.112           0.076   
N                 113.000         172.000         107.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 11&quot; | v_negative==0) , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 11&quot; | v_negative==0) , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.042           0.212           0.366   
                  (0.395)         (0.384)         (0.319)   
wp_right2          -0.269           0.080          -0.286   
                  (0.489)         (0.201)         (0.269)   
c.neg#c.wp~2        0.781          -0.235          -0.964   
                  (0.974)         (0.585)         (0.497)   
vid_order          -0.141***       -0.058***       -0.086***
                  (0.037)         (0.014)         (0.023)   
female             -0.138          -0.132*         -0.070   
                  (0.150)         (0.060)         (0.098)   
age                -0.005           0.001           0.002   
                  (0.008)         (0.003)         (0.007)   
income             -0.342           0.145           0.072   
                  (0.369)         (0.124)         (0.202)   
university          0.007          -0.006          -0.219   
                  (0.149)         (0.063)         (0.117)   
_cons               1.050*          0.088           0.434   
                  (0.414)         (0.172)         (0.269)   
------------------------------------------------------------
r2_w                0.143           0.077           0.125   
r2_b                0.025           0.194           0.253   
r2_o                0.110           0.117           0.149   
N                 158.000         186.000         152.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.188           0.624           0.058   
                  (0.254)         (0.504)         (0.187)   
wp_right2          -0.221          -0.539           0.161   
                  (0.484)         (0.512)         (0.305)   
c.neg#c.wp~2        0.156          -0.935           0.184   
                  (0.893)         (1.299)         (0.650)   
vid_order          -0.144***       -0.047          -0.072***
                  (0.033)         (0.042)         (0.020)   
female             -0.068           0.093          -0.142   
                  (0.144)         (0.190)         (0.090)   
age                -0.036           0.002           0.000   
                  (0.025)         (0.051)         (0.009)   
income             -0.259          -0.196           0.338   
                  (0.327)         (0.477)         (0.253)   
university         -0.244          -0.110           0.257   
                  (0.203)         (0.352)         (0.143)   
_cons               1.754*          0.322          -0.093   
                  (0.736)         (1.123)         (0.359)   
------------------------------------------------------------
r2_w                0.078           0.036           0.127   
r2_b                0.177           0.219           0.170   
r2_o                0.115           0.067           0.152   
N                 222.000         102.000         115.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_11
&gt; &quot; | v_negative==0) , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.276           0.224           1.139**        -0.392   
                  (0.641)         (0.226)         (0.401)         (0.224)   
wp_right2           0.376           0.241           0.234           0.003   
                  (0.699)         (0.328)         (0.337)         (0.197)   
c.neg#c.wp~2        0.019          -0.616          -1.701**         0.607   
                  (1.601)         (0.684)         (0.657)         (0.371)   
vid_order          -0.107*         -0.074**        -0.082**        -0.033*  
                  (0.048)         (0.028)         (0.031)         (0.014)   
female              0.266           0.077           0.032           0.025   
                  (0.204)         (0.131)         (0.122)         (0.065)   
age                -0.023          -0.001           0.009           0.002   
                  (0.068)         (0.003)         (0.006)         (0.003)   
income             -0.603           0.237          -0.248          -0.053   
                  (0.385)         (0.214)         (0.310)         (0.202)   
university          0.057          -0.041          -0.034           0.047   
                  (0.310)         (0.128)         (0.179)         (0.063)   
_cons               0.853           0.034          -0.022           0.082   
                  (1.553)         (0.259)         (0.377)         (0.187)   
----------------------------------------------------------------------------
r2_w                0.086           0.100           0.212           0.067   
r2_b                0.205           0.067           0.072           0.074   
r2_o                0.119           0.090           0.180           0.072   
N                 111.000          97.000          97.000         146.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.205          -0.192           0.001   
                  (0.229)         (0.264)         (0.155)   
wp_right2          -0.059          -0.217           0.073   
                  (0.264)         (0.324)         (0.236)   
c.neg#c.wp~2        0.605           0.842           0.175   
                  (0.539)         (0.710)         (0.378)   
vid_order          -0.035          -0.112***       -0.040** 
                  (0.025)         (0.027)         (0.014)   
female              0.187          -0.121          -0.043   
                  (0.114)         (0.110)         (0.089)   
age                 0.005          -0.002           0.004   
                  (0.004)         (0.004)         (0.004)   
income             -0.620*          0.098          -0.062   
                  (0.288)         (0.223)         (0.173)   
university          0.019          -0.180           0.162   
                  (0.115)         (0.147)         (0.089)   
_cons               0.243           0.656**        -0.103   
                  (0.264)         (0.249)         (0.200)   
------------------------------------------------------------
r2_w                0.046           0.131           0.018   
r2_b                0.302           0.203           0.046   
r2_o                0.146           0.156           0.032   
N                  97.000         140.000         565.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negative
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12&quot; | v_negative==0
&gt; ) , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 12&quot; | v_negative==0) , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 12&quot; | v_negative==0) , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.005          -0.470          -0.029          -0.283   
                  (0.063)         (0.393)         (0.259)         (0.158)   
wp_right2           0.020          -0.409          -0.407          -0.386   
                  (0.070)         (0.453)         (0.755)         (0.277)   
c.neg#c.wp~2        0.264           1.973*          0.586           0.284   
                  (0.141)         (1.002)         (0.844)         (0.480)   
vid_order          -0.078***       -0.032          -0.130**        -0.037   
                  (0.007)         (0.037)         (0.041)         (0.023)   
female             -0.028          -0.007           0.223           0.072   
                  (0.029)         (0.159)         (0.308)         (0.132)   
age                 0.001           0.021           0.041          -0.004   
                  (0.001)         (0.015)         (0.031)         (0.005)   
income              0.005          -0.298          -0.117           0.078   
                  (0.060)         (0.378)         (0.545)         (0.257)   
university         -0.007           0.114          -0.210          -0.119   
                  (0.030)         (0.166)         (0.418)         (0.141)   
_cons               0.210**        -0.168          -0.529           0.466   
                  (0.070)         (0.455)         (0.965)         (0.304)   
----------------------------------------------------------------------------
r2_w                0.057           0.068           0.161           0.156   
r2_b                0.039           0.123           0.110           0.092   
r2_o                0.050           0.088           0.154           0.118   
N                2893.000         105.000         103.000          80.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.279           0.070          -0.439   
                  (0.363)         (0.523)         (0.265)   
wp_right2           0.697          -0.226          -0.218   
                  (0.579)         (0.533)         (0.387)   
c.neg#c.wp~2        1.160          -0.120           1.686*  
                  (1.068)         (1.033)         (0.818)   
vid_order          -0.137***       -0.099***       -0.040   
                  (0.040)         (0.030)         (0.027)   
female              0.119          -0.100          -0.040   
                  (0.188)         (0.135)         (0.123)   
age                -0.000          -0.008           0.001   
                  (0.008)         (0.014)         (0.004)   
income              0.578           0.306           0.422   
                  (0.537)         (0.329)         (0.274)   
university          0.305          -0.046          -0.034   
                  (0.191)         (0.202)         (0.124)   
_cons              -0.354           0.630          -0.077   
                  (0.489)         (0.490)         (0.293)   
------------------------------------------------------------
r2_w                0.201           0.050           0.038   
r2_b                0.146           0.191           0.273   
r2_o                0.153           0.081           0.088   
N                 112.000         173.000         107.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 12&quot; | v_negative==0) , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 12&quot; | v_negative==0) , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.188           0.440           0.160   
                  (0.368)         (0.254)         (0.294)   
wp_right2          -0.184           0.125          -0.211   
                  (0.468)         (0.214)         (0.302)   
c.neg#c.wp~2        0.848          -0.391          -0.282   
                  (0.932)         (0.396)         (0.468)   
vid_order          -0.162***       -0.079***       -0.099***
                  (0.034)         (0.016)         (0.021)   
female             -0.170          -0.165*         -0.024   
                  (0.144)         (0.065)         (0.114)   
age                -0.006           0.001          -0.003   
                  (0.007)         (0.003)         (0.008)   
income             -0.207           0.105           0.289   
                  (0.362)         (0.126)         (0.234)   
university          0.059          -0.056          -0.204   
                  (0.143)         (0.068)         (0.133)   
_cons               1.033**         0.192           0.465   
                  (0.400)         (0.186)         (0.307)   
------------------------------------------------------------
r2_w                0.161           0.170           0.158   
r2_b                0.146           0.220           0.129   
r2_o                0.155           0.184           0.135   
N                 157.000         185.000         161.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.434          -0.811           0.184   
                  (0.276)         (0.587)         (0.197)   
wp_right2          -0.139          -0.466           0.187   
                  (0.498)         (0.530)         (0.329)   
c.neg#c.wp~2        1.815           1.823          -0.690   
                  (0.986)         (1.578)         (0.698)   
vid_order          -0.159***       -0.088          -0.067** 
                  (0.035)         (0.048)         (0.021)   
female             -0.050           0.180          -0.144   
                  (0.148)         (0.206)         (0.100)   
age                -0.021           0.007           0.002   
                  (0.025)         (0.054)         (0.009)   
income             -0.325           0.133           0.267   
                  (0.335)         (0.516)         (0.269)   
university         -0.247          -0.125           0.275   
                  (0.216)         (0.396)         (0.155)   
_cons               1.469*          0.173          -0.141   
                  (0.745)         (1.202)         (0.378)   
------------------------------------------------------------
r2_w                0.062           0.075           0.113   
r2_b                0.311           0.090           0.126   
r2_o                0.125           0.077           0.138   
N                 221.000          95.000         113.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_12
&gt; &quot; | v_negative==0) , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.014           0.113          -0.137          -0.127   
                  (0.563)         (0.217)         (0.383)         (0.244)   
wp_right2          -0.113           0.119           0.270          -0.047   
                  (0.679)         (0.328)         (0.360)         (0.174)   
c.neg#c.wp~2        0.373           0.381           0.339           0.260   
                  (1.470)         (0.594)         (0.642)         (0.376)   
vid_order          -0.061          -0.088***       -0.040          -0.028*  
                  (0.046)         (0.025)         (0.033)         (0.013)   
female             -0.062          -0.019           0.199          -0.009   
                  (0.205)         (0.130)         (0.135)         (0.055)   
age                -0.100          -0.004           0.008           0.004   
                  (0.065)         (0.003)         (0.007)         (0.003)   
income             -0.654           0.015          -0.099           0.062   
                  (0.381)         (0.203)         (0.340)         (0.168)   
university          0.245           0.099          -0.084          -0.000   
                  (0.315)         (0.125)         (0.212)         (0.055)   
_cons               2.506           0.349          -0.314          -0.000   
                  (1.491)         (0.241)         (0.415)         (0.167)   
----------------------------------------------------------------------------
r2_w                0.024           0.127           0.010           0.036   
r2_b                0.208           0.307           0.274           0.137   
r2_o                0.080           0.167           0.105           0.068   
N                 109.000         105.000          94.000         143.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.149           0.129           0.211   
                  (0.216)         (0.194)         (0.157)   
wp_right2           0.032          -0.274           0.127   
                  (0.262)         (0.383)         (0.213)   
c.neg#c.wp~2        0.244           0.082           0.061   
                  (0.539)         (0.569)         (0.363)   
vid_order          -0.016          -0.100***       -0.042** 
                  (0.025)         (0.024)         (0.015)   
female              0.166          -0.201          -0.040   
                  (0.108)         (0.132)         (0.078)   
age                 0.001          -0.003           0.002   
                  (0.004)         (0.005)         (0.003)   
income             -0.568*          0.228          -0.081   
                  (0.285)         (0.266)         (0.152)   
university          0.033          -0.122           0.137   
                  (0.108)         (0.180)         (0.078)   
_cons               0.275           0.648*         -0.042   
                  (0.258)         (0.284)         (0.180)   
------------------------------------------------------------
r2_w                0.020           0.106           0.046   
r2_b                0.316           0.279           0.023   
r2_o                0.094           0.160           0.037   
N                 102.000         147.000         581.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.    
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negative
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13&quot; | v_negative==0
&gt; ) , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 13&quot; | v_negative==0) , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 13&quot; | v_negative==0) , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.132*         -0.325          -0.338          -0.270   
                  (0.063)         (0.393)         (0.286)         (0.169)   
wp_right2           0.012          -0.443          -0.656          -0.331   
                  (0.068)         (0.450)         (0.651)         (0.253)   
c.neg#c.wp~2        0.169          -0.045           1.548           0.619   
                  (0.140)         (0.941)         (0.954)         (0.500)   
vid_order          -0.083***       -0.027          -0.131**        -0.043   
                  (0.006)         (0.037)         (0.045)         (0.024)   
female             -0.043          -0.100           0.153           0.117   
                  (0.028)         (0.155)         (0.247)         (0.118)   
age                 0.002*         -0.003           0.037          -0.004   
                  (0.001)         (0.015)         (0.025)         (0.004)   
income             -0.001          -0.081          -0.230          -0.110   
                  (0.058)         (0.336)         (0.430)         (0.227)   
university         -0.013           0.074          -0.289          -0.045   
                  (0.029)         (0.167)         (0.336)         (0.118)   
_cons               0.210**         0.380          -0.226           0.479   
                  (0.068)         (0.471)         (0.805)         (0.275)   
----------------------------------------------------------------------------
r2_w                0.061           0.050           0.158           0.061   
r2_b                0.051           0.089           0.191           0.124   
r2_o                0.057           0.061           0.170           0.080   
N                2911.000         115.000         104.000          84.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.251          -1.117*          0.113   
                  (0.313)         (0.516)         (0.230)   
wp_right2           0.897          -0.477          -0.181   
                  (0.486)         (0.539)         (0.358)   
c.neg#c.wp~2       -0.660           1.999          -0.240   
                  (0.828)         (1.025)         (0.696)   
vid_order          -0.105***       -0.105***       -0.040   
                  (0.032)         (0.030)         (0.025)   
female              0.095           0.018          -0.045   
                  (0.159)         (0.134)         (0.114)   
age                 0.008          -0.007          -0.001   
                  (0.007)         (0.013)         (0.004)   
income              0.504           0.406           0.259   
                  (0.460)         (0.329)         (0.255)   
university          0.389*          0.047          -0.012   
                  (0.163)         (0.210)         (0.111)   
_cons              -0.863*          0.573           0.044   
                  (0.405)         (0.477)         (0.265)   
------------------------------------------------------------
r2_w                0.176           0.101           0.053   
r2_b                0.243           0.142           0.012   
r2_o                0.207           0.112           0.038   
N                 113.000         179.000         107.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 13&quot; | v_negative==0) , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 13&quot; | v_negative==0) , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.217           0.200          -0.192   
                  (0.397)         (0.247)         (0.338)   
wp_right2          -0.141           0.120          -0.202   
                  (0.490)         (0.210)         (0.263)   
c.neg#c.wp~2       -0.682          -0.418           0.340   
                  (1.006)         (0.383)         (0.517)   
vid_order          -0.152***       -0.080***       -0.098***
                  (0.036)         (0.015)         (0.022)   
female             -0.173          -0.130*         -0.033   
                  (0.156)         (0.063)         (0.095)   
age                -0.007           0.001          -0.003   
                  (0.008)         (0.003)         (0.007)   
income             -0.089           0.107           0.180   
                  (0.374)         (0.127)         (0.197)   
university         -0.078          -0.030          -0.154   
                  (0.152)         (0.066)         (0.111)   
_cons               1.012*          0.172           0.508   
                  (0.410)         (0.182)         (0.259)   
------------------------------------------------------------
r2_w                0.115           0.141           0.146   
r2_b                0.138           0.187           0.091   
r2_o                0.135           0.159           0.135   
N                 151.000         190.000         159.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.251           0.329          -0.029   
                  (0.279)         (0.434)         (0.200)   
wp_right2          -0.190          -0.487           0.113   
                  (0.504)         (0.448)         (0.314)   
c.neg#c.wp~2        0.547          -0.500           0.189   
                  (0.947)         (1.153)         (0.683)   
vid_order          -0.175***       -0.085*         -0.059** 
                  (0.036)         (0.039)         (0.020)   
female             -0.174           0.133          -0.200*  
                  (0.149)         (0.169)         (0.096)   
age                -0.009           0.002          -0.006   
                  (0.026)         (0.045)         (0.009)   
income             -0.382          -0.027           0.351   
                  (0.331)         (0.439)         (0.253)   
university         -0.450*         -0.087           0.249   
                  (0.210)         (0.309)         (0.148)   
_cons               1.518*          0.329           0.063   
                  (0.771)         (1.012)         (0.372)   
------------------------------------------------------------
r2_w                0.089           0.080           0.093   
r2_b                0.210           0.120           0.234   
r2_o                0.132           0.099           0.129   
N                 223.000         100.000         114.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_13
&gt; &quot; | v_negative==0) , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.010          -0.284          -0.179          -0.159   
                  (0.556)         (0.227)         (0.408)         (0.189)   
wp_right2           0.100           0.177           0.274          -0.026   
                  (0.644)         (0.315)         (0.432)         (0.177)   
c.neg#c.wp~2       -0.703           0.675           0.380           0.196   
                  (1.384)         (0.603)         (0.681)         (0.307)   
vid_order          -0.059          -0.083**        -0.071**        -0.028*  
                  (0.044)         (0.027)         (0.028)         (0.012)   
female              0.026           0.028           0.062           0.010   
                  (0.194)         (0.121)         (0.176)         (0.057)   
age                -0.059          -0.001           0.006           0.005   
                  (0.061)         (0.003)         (0.009)         (0.003)   
income             -0.565           0.203          -0.232           0.016   
                  (0.356)         (0.200)         (0.446)         (0.171)   
university          0.248           0.009          -0.020           0.023   
                  (0.289)         (0.117)         (0.268)         (0.056)   
_cons               1.462           0.111          -0.068          -0.031   
                  (1.392)         (0.241)         (0.494)         (0.169)   
----------------------------------------------------------------------------
r2_w                0.065           0.102           0.081           0.062   
r2_b                0.113           0.241           0.148           0.102   
r2_o                0.086           0.124           0.106           0.077   
N                 111.000         101.000          96.000         147.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.227          -0.547**        -0.170   
                  (0.213)         (0.206)         (0.160)   
wp_right2          -0.070          -0.344           0.108   
                  (0.251)         (0.426)         (0.219)   
c.neg#c.wp~2        0.163           1.315*          0.180   
                  (0.513)         (0.554)         (0.379)   
vid_order          -0.021          -0.090***       -0.054***
                  (0.025)         (0.022)         (0.015)   
female              0.201          -0.217          -0.042   
                  (0.104)         (0.150)         (0.081)   
age                 0.005          -0.000           0.005   
                  (0.004)         (0.006)         (0.003)   
income             -0.397           0.229          -0.027   
                  (0.267)         (0.301)         (0.158)   
university         -0.040          -0.128           0.084   
                  (0.105)         (0.207)         (0.080)   
_cons               0.075           0.516          -0.065   
                  (0.244)         (0.307)         (0.185)   
------------------------------------------------------------
r2_w                0.060           0.144           0.039   
r2_b                0.251           0.206           0.025   
r2_o                0.104           0.178           0.033   
N                 102.000         146.000         569.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negative
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14&quot; | v_negative==0
&gt; ) , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 14&quot; | v_negative==0) , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 14&quot; | v_negative==0) , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.184**         0.683           0.107          -0.028   
                  (0.064)         (0.403)         (0.328)         (0.166)   
wp_right2           0.022          -0.459          -0.459          -0.266   
                  (0.071)         (0.422)         (0.726)         (0.314)   
c.neg#c.wp~2        0.049          -0.860           1.403          -0.063   
                  (0.142)         (0.978)         (1.053)         (0.542)   
vid_order          -0.073***       -0.015          -0.106*         -0.045*  
                  (0.007)         (0.037)         (0.045)         (0.022)   
female             -0.009          -0.079           0.382           0.122   
                  (0.029)         (0.150)         (0.293)         (0.151)   
age                 0.001          -0.006           0.050          -0.004   
                  (0.001)         (0.014)         (0.031)         (0.005)   
income             -0.016           0.201          -0.303           0.129   
                  (0.061)         (0.338)         (0.503)         (0.296)   
university         -0.008           0.023          -0.246          -0.040   
                  (0.031)         (0.155)         (0.398)         (0.153)   
_cons               0.183**         0.292          -0.812           0.365   
                  (0.070)         (0.452)         (0.920)         (0.324)   
----------------------------------------------------------------------------
r2_w                0.065           0.071           0.117           0.085   
r2_b                0.035           0.091           0.249           0.078   
r2_o                0.054           0.079           0.191           0.092   
N                2886.000         105.000          98.000          80.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.204           0.408           0.228   
                  (0.328)         (0.643)         (0.265)   
wp_right2           0.454          -0.331          -0.008   
                  (0.547)         (0.538)         (0.368)   
c.neg#c.wp~2       -0.395          -0.286          -0.189   
                  (0.831)         (1.225)         (0.726)   
vid_order          -0.146***       -0.108***       -0.032   
                  (0.034)         (0.030)         (0.025)   
female              0.236          -0.055           0.065   
                  (0.179)         (0.136)         (0.117)   
age                 0.009          -0.006          -0.000   
                  (0.008)         (0.013)         (0.004)   
income             -0.160           0.470           0.123   
                  (0.532)         (0.315)         (0.259)   
university          0.331          -0.043           0.042   
                  (0.182)         (0.210)         (0.115)   
_cons              -0.357           0.569          -0.050   
                  (0.464)         (0.481)         (0.281)   
------------------------------------------------------------
r2_w                0.208           0.087           0.045   
r2_b                0.159           0.213           0.039   
r2_o                0.189           0.114           0.043   
N                 115.000         176.000         106.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 14&quot; | v_negative==0) , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_
&gt; 14&quot; | v_negative==0) , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.316           0.334           0.244   
                  (0.337)         (0.268)         (0.327)   
wp_right2          -0.085           0.096          -0.227   
                  (0.491)         (0.247)         (0.263)   
c.neg#c.wp~2       -0.133          -0.409           0.028   
                  (0.835)         (0.414)         (0.504)   
vid_order          -0.094**        -0.066***       -0.083***
                  (0.033)         (0.015)         (0.022)   
female             -0.040          -0.153          -0.052   
                  (0.152)         (0.079)         (0.098)   
age                -0.007           0.001          -0.000   
                  (0.008)         (0.004)         (0.007)   
income              0.153           0.170           0.072   
                  (0.363)         (0.156)         (0.202)   
university         -0.035          -0.028          -0.145   
                  (0.151)         (0.083)         (0.113)   
_cons               0.509           0.115           0.422   
                  (0.404)         (0.215)         (0.262)   
------------------------------------------------------------
r2_w                0.099           0.121           0.124   
r2_b                0.046           0.154           0.140   
r2_o                0.088           0.148           0.134   
N                 161.000         186.000         156.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.025          -0.141           0.166   
                  (0.261)         (0.468)         (0.173)   
wp_right2          -0.190          -0.527           0.093   
                  (0.527)         (0.488)         (0.302)   
c.neg#c.wp~2        0.424           0.912          -0.152   
                  (0.916)         (1.131)         (0.663)   
vid_order          -0.163***       -0.075          -0.048*  
                  (0.034)         (0.042)         (0.019)   
female             -0.215           0.247          -0.149   
                  (0.158)         (0.181)         (0.089)   
age                -0.023           0.004          -0.005   
                  (0.028)         (0.048)         (0.009)   
income             -0.482          -0.238           0.341   
                  (0.355)         (0.450)         (0.246)   
university         -0.269          -0.075           0.149   
                  (0.226)         (0.318)         (0.140)   
_cons               1.741*          0.285           0.043   
                  (0.819)         (1.049)         (0.351)   
------------------------------------------------------------
r2_w                0.089           0.044           0.126   
r2_b                0.241           0.180           0.058   
r2_o                0.135           0.079           0.104   
N                 226.000         103.000         116.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; (stimulus==&quot;v_14
&gt; &quot; | v_negative==0) , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.451          -0.428          -0.284           0.219   
                  (0.453)         (0.239)         (0.339)         (0.231)   
wp_right2           0.169           0.104           0.279          -0.101   
                  (0.666)         (0.318)         (0.427)         (0.207)   
c.neg#c.wp~2       -0.266           1.239*          0.747          -0.216   
                  (1.143)         (0.610)         (0.558)         (0.366)   
vid_order          -0.084          -0.080**        -0.058          -0.031*  
                  (0.044)         (0.025)         (0.031)         (0.013)   
female              0.039          -0.018           0.240           0.057   
                  (0.197)         (0.123)         (0.169)         (0.071)   
age                -0.055          -0.003           0.006           0.005   
                  (0.064)         (0.003)         (0.009)         (0.003)   
income             -0.526           0.026          -0.325           0.170   
                  (0.348)         (0.208)         (0.437)         (0.209)   
university         -0.023           0.086          -0.023           0.009   
                  (0.306)         (0.121)         (0.258)         (0.068)   
_cons               1.662           0.282          -0.160          -0.047   
                  (1.456)         (0.242)         (0.491)         (0.192)   
----------------------------------------------------------------------------
r2_w                0.060           0.134           0.076           0.066   
r2_b                0.179           0.224           0.260           0.132   
r2_o                0.096           0.157           0.160           0.097   
N                 113.000         100.000          98.000         140.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.216           0.146           0.385*  
                  (0.222)         (0.219)         (0.175)   
wp_right2          -0.006          -0.249           0.115   
                  (0.251)         (0.429)         (0.212)   
c.neg#c.wp~2        0.810           0.378          -0.231   
                  (0.652)         (0.645)         (0.407)   
vid_order          -0.022          -0.082**        -0.036*  
                  (0.025)         (0.027)         (0.015)   
female              0.164          -0.134           0.006   
                  (0.104)         (0.150)         (0.077)   
age                 0.002          -0.001           0.004   
                  (0.004)         (0.006)         (0.003)   
income             -0.448          -0.068          -0.006   
                  (0.276)         (0.301)         (0.151)   
university          0.016          -0.181           0.081   
                  (0.108)         (0.203)         (0.078)   
_cons               0.219           0.596          -0.144   
                  (0.247)         (0.313)         (0.179)   
------------------------------------------------------------
r2_w                0.033           0.102           0.054   
r2_b                0.239           0.132           0.013   
r2_o                0.085           0.106           0.035   
N                  97.000         146.000         564.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.         
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(56,936 real changes made, 39,228 to missing)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.101**        -0.299          -0.042   
                  (0.032)         (0.179)         (0.127)   
wp_right2           0.027          -0.062           0.081   
                  (0.021)         (0.138)         (0.129)   
c.neg#c.wp~2       -0.128           1.102*          0.364   
                  (0.070)         (0.436)         (0.384)   
pho_order           0.004***        0.011***        0.009** 
                  (0.001)         (0.003)         (0.003)   
female              0.001           0.007           0.110   
                  (0.009)         (0.051)         (0.063)   
age                -0.000           0.004           0.000   
                  (0.000)         (0.005)         (0.002)   
income              0.003          -0.087          -0.109   
                  (0.019)         (0.110)         (0.122)   
university          0.006           0.020           0.140*  
                  (0.009)         (0.051)         (0.065)   
_cons              -0.076***       -0.235          -0.258   
                  (0.022)         (0.148)         (0.138)   
------------------------------------------------------------
r2_w                0.005           0.055           0.027   
r2_b                0.017           0.075           0.283   
r2_o                0.005           0.055           0.054   
N                8834.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.157          -0.108           0.139   
                  (0.154)         (0.226)         (0.077)   
wp_right2          -0.279*          0.013           0.035   
                  (0.142)         (0.159)         (0.099)   
c.neg#c.wp~2        0.772           0.232          -0.282   
                  (0.415)         (0.442)         (0.227)   
pho_order           0.005           0.003           0.004*  
                  (0.003)         (0.003)         (0.002)   
female              0.049           0.002          -0.026   
                  (0.050)         (0.043)         (0.034)   
age                -0.001          -0.003           0.001   
                  (0.002)         (0.004)         (0.001)   
income             -0.051           0.089           0.011   
                  (0.144)         (0.112)         (0.072)   
university         -0.069          -0.001           0.018   
                  (0.051)         (0.062)         (0.033)   
_cons               0.075          -0.029          -0.126   
                  (0.129)         (0.146)         (0.075)   
------------------------------------------------------------
r2_w                0.019           0.002           0.027   
r2_b                0.139           0.025           0.058   
r2_o                0.028           0.005           0.031   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.146           0.008           0.456*          0.090   
                  (0.142)         (0.154)         (0.178)         (0.136)   
wp_right2           0.137          -0.025           0.083           0.286   
                  (0.120)         (0.089)         (0.090)         (0.206)   
c.neg#c.wp~2       -0.184          -0.087          -0.706*         -0.222   
                  (0.356)         (0.236)         (0.275)         (0.380)   
pho_order           0.007**         0.004*          0.003           0.003   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female             -0.006           0.012          -0.006           0.034   
                  (0.038)         (0.030)         (0.034)         (0.070)   
age                 0.001          -0.001          -0.001           0.007   
                  (0.002)         (0.001)         (0.002)         (0.009)   
income             -0.076          -0.002           0.032          -0.005   
                  (0.092)         (0.059)         (0.075)         (0.141)   
university          0.048          -0.007          -0.010          -0.029   
                  (0.038)         (0.031)         (0.040)         (0.099)   
_cons              -0.227*         -0.016          -0.077          -0.266   
                  (0.099)         (0.079)         (0.095)         (0.291)   
----------------------------------------------------------------------------
r2_w                0.016           0.008           0.018           0.005   
r2_b                0.227           0.035           0.005           0.139   
r2_o                0.027           0.011           0.017           0.022   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.250           0.038           0.174   
                  (0.206)         (0.094)         (0.242)   
wp_right2          -0.093          -0.013          -0.092   
                  (0.170)         (0.102)         (0.214)   
c.neg#c.wp~2        0.369           0.219          -0.246   
                  (0.507)         (0.330)         (0.625)   
pho_order           0.011**         0.005**        -0.006   
                  (0.004)         (0.002)         (0.004)   
female             -0.134*         -0.032          -0.046   
                  (0.066)         (0.032)         (0.065)   
age                 0.026          -0.002          -0.009   
                  (0.017)         (0.003)         (0.021)   
income              0.002           0.034           0.156   
                  (0.158)         (0.089)         (0.126)   
university          0.078          -0.013           0.007   
                  (0.178)         (0.048)         (0.102)   
_cons              -0.603          -0.009           0.260   
                  (0.371)         (0.118)         (0.491)   
------------------------------------------------------------
r2_w                0.025           0.031           0.012   
r2_b                0.278           0.042           0.077   
r2_o                0.055           0.032           0.015   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_1202&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.348**        -0.167           0.122   
                  (0.122)         (0.176)         (0.110)   
wp_right2           0.030           0.148          -0.039   
                  (0.120)         (0.091)         (0.057)   
c.neg#c.wp~2       -0.682*          0.360          -0.128   
                  (0.322)         (0.289)         (0.175)   
pho_order           0.001          -0.000           0.001   
                  (0.003)         (0.003)         (0.001)   
female              0.030          -0.043           0.031   
                  (0.048)         (0.038)         (0.020)   
age                 0.001          -0.002           0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.042           0.025          -0.050   
                  (0.076)         (0.096)         (0.059)   
university          0.011          -0.080          -0.008   
                  (0.046)         (0.058)         (0.019)   
_cons              -0.108           0.030           0.017   
                  (0.094)         (0.110)         (0.056)   
------------------------------------------------------------
r2_w                0.026           0.006           0.006   
r2_b                0.079           0.266           0.172   
r2_o                0.032           0.027           0.014   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.386***        0.034           0.197   
                  (0.102)         (0.130)         (0.108)   
wp_right2          -0.113           0.047           0.054   
                  (0.117)         (0.123)         (0.085)   
c.neg#c.wp~2       -0.690**        -0.043          -0.341   
                  (0.258)         (0.369)         (0.273)   
pho_order           0.003           0.003           0.002   
                  (0.002)         (0.003)         (0.002)   
female              0.017           0.032          -0.002   
                  (0.053)         (0.044)         (0.028)   
age                 0.004*         -0.002          -0.001   
                  (0.002)         (0.002)         (0.001)   
income              0.094          -0.111           0.112   
                  (0.136)         (0.088)         (0.058)   
university          0.003          -0.067           0.037   
                  (0.054)         (0.060)         (0.029)   
_cons              -0.312**         0.073          -0.131   
                  (0.116)         (0.094)         (0.068)   
------------------------------------------------------------
r2_w                0.048           0.002           0.004   
r2_b                0.216           0.104           0.049   
r2_o                0.081           0.012           0.008   
N                 338.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                 
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.014          -0.036           0.165   
                  (0.032)         (0.167)         (0.133)   
wp_right2           0.027          -0.062           0.095   
                  (0.021)         (0.129)         (0.170)   
c.neg#c.wp~2       -0.036          -0.148          -0.626   
                  (0.069)         (0.406)         (0.400)   
pho_order           0.004***        0.009**         0.008*  
                  (0.001)         (0.003)         (0.004)   
female              0.000           0.018           0.131   
                  (0.009)         (0.047)         (0.085)   
age                -0.000          -0.001           0.001   
                  (0.000)         (0.005)         (0.003)   
income             -0.001          -0.076          -0.137   
                  (0.019)         (0.102)         (0.164)   
university          0.008           0.015           0.184*  
                  (0.009)         (0.048)         (0.088)   
_cons              -0.077***       -0.118          -0.295   
                  (0.021)         (0.138)         (0.179)   
------------------------------------------------------------
r2_w                0.005           0.037           0.030   
r2_b                0.009           0.042           0.255   
r2_o                0.005           0.037           0.066   
N                8835.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.153           0.017          -0.050   
                  (0.147)         (0.230)         (0.069)   
wp_right2          -0.244           0.062           0.014   
                  (0.146)         (0.153)         (0.117)   
c.neg#c.wp~2        0.160          -0.117           0.144   
                  (0.397)         (0.450)         (0.203)   
pho_order           0.006           0.001           0.004** 
                  (0.003)         (0.003)         (0.001)   
female              0.053          -0.025          -0.033   
                  (0.052)         (0.041)         (0.040)   
age                -0.001          -0.001           0.001   
                  (0.002)         (0.004)         (0.001)   
income              0.039           0.043           0.035   
                  (0.150)         (0.107)         (0.085)   
university         -0.062           0.005           0.000   
                  (0.053)         (0.060)         (0.040)   
_cons               0.002          -0.041          -0.131   
                  (0.131)         (0.141)         (0.087)   
------------------------------------------------------------
r2_w                0.017           0.001           0.022   
r2_b                0.128           0.028           0.087   
r2_o                0.028           0.002           0.036   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.070           0.167           0.151          -0.067   
                  (0.138)         (0.156)         (0.169)         (0.132)   
wp_right2           0.116          -0.022           0.087           0.354   
                  (0.116)         (0.086)         (0.086)         (0.204)   
c.neg#c.wp~2       -0.214          -0.263          -0.371          -0.122   
                  (0.344)         (0.239)         (0.261)         (0.370)   
pho_order           0.009***        0.004*          0.002           0.004   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female              0.012           0.024           0.015           0.055   
                  (0.037)         (0.029)         (0.033)         (0.069)   
age                 0.002          -0.001          -0.002           0.011   
                  (0.002)         (0.001)         (0.002)         (0.009)   
income             -0.089          -0.013          -0.015           0.061   
                  (0.089)         (0.057)         (0.072)         (0.140)   
university          0.055          -0.003           0.019          -0.044   
                  (0.037)         (0.030)         (0.038)         (0.098)   
_cons              -0.264**        -0.010          -0.039          -0.424   
                  (0.096)         (0.077)         (0.091)         (0.286)   
----------------------------------------------------------------------------
r2_w                0.022           0.010           0.011           0.015   
r2_b                0.236           0.050           0.027           0.203   
r2_o                0.034           0.015           0.012           0.042   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.105          -0.027          -0.291   
                  (0.206)         (0.090)         (0.239)   
wp_right2          -0.089          -0.027          -0.187   
                  (0.174)         (0.098)         (0.212)   
c.neg#c.wp~2        0.317           0.190           1.036   
                  (0.506)         (0.318)         (0.617)   
pho_order           0.010**         0.005**        -0.002   
                  (0.004)         (0.002)         (0.004)   
female             -0.103          -0.069*         -0.112   
                  (0.067)         (0.031)         (0.065)   
age                 0.023          -0.005          -0.022   
                  (0.017)         (0.003)         (0.021)   
income              0.044           0.081           0.099   
                  (0.162)         (0.086)         (0.125)   
university          0.120           0.028           0.007   
                  (0.181)         (0.047)         (0.100)   
_cons              -0.610           0.024           0.570   
                  (0.380)         (0.114)         (0.483)   
------------------------------------------------------------
r2_w                0.017           0.024           0.010   
r2_b                0.221           0.237           0.159   
r2_o                0.040           0.038           0.022   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_2683&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.076          -0.161           0.058   
                  (0.117)         (0.165)         (0.103)   
wp_right2           0.012           0.141          -0.026   
                  (0.115)         (0.086)         (0.054)   
c.neg#c.wp~2       -0.051           0.191          -0.159   
                  (0.307)         (0.271)         (0.165)   
pho_order           0.004           0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.018          -0.048           0.018   
                  (0.046)         (0.035)         (0.018)   
age                 0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.039           0.011          -0.065   
                  (0.073)         (0.090)         (0.056)   
university          0.029          -0.092          -0.005   
                  (0.044)         (0.054)         (0.018)   
_cons              -0.137           0.020           0.034   
                  (0.090)         (0.103)         (0.053)   
------------------------------------------------------------
r2_w                0.004           0.004           0.007   
r2_b                0.135           0.319           0.126   
r2_o                0.016           0.029           0.013   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.070          -0.046          -0.109   
                  (0.096)         (0.129)         (0.106)   
wp_right2          -0.125           0.048           0.059   
                  (0.104)         (0.121)         (0.084)   
c.neg#c.wp~2       -0.121           0.089           0.103   
                  (0.243)         (0.365)         (0.268)   
pho_order           0.002           0.003           0.003   
                  (0.002)         (0.003)         (0.002)   
female             -0.021           0.029           0.011   
                  (0.047)         (0.043)         (0.028)   
age                 0.004*         -0.002          -0.001   
                  (0.002)         (0.002)         (0.001)   
income              0.137          -0.135           0.116*  
                  (0.120)         (0.086)         (0.057)   
university         -0.035          -0.029           0.040   
                  (0.048)         (0.059)         (0.029)   
_cons              -0.249*          0.066          -0.149*  
                  (0.104)         (0.093)         (0.067)   
------------------------------------------------------------
r2_w                0.004           0.002           0.004   
r2_b                0.266           0.092           0.059   
r2_o                0.043           0.010           0.008   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                 
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.018          -0.095          -0.084   
                  (0.032)         (0.165)         (0.127)   
wp_right2           0.024          -0.071           0.072   
                  (0.021)         (0.128)         (0.131)   
c.neg#c.wp~2       -0.058           0.099           0.994** 
                  (0.069)         (0.400)         (0.383)   
pho_order           0.004***        0.011***        0.007*  
                  (0.001)         (0.003)         (0.003)   
female             -0.003           0.019           0.098   
                  (0.009)         (0.047)         (0.064)   
age                -0.000          -0.002           0.000   
                  (0.000)         (0.005)         (0.002)   
income             -0.017          -0.034          -0.158   
                  (0.019)         (0.102)         (0.124)   
university          0.003           0.013           0.143*  
                  (0.009)         (0.048)         (0.067)   
_cons              -0.065**        -0.119          -0.205   
                  (0.022)         (0.136)         (0.141)   
------------------------------------------------------------
r2_w                0.004           0.040           0.056   
r2_b                0.012           0.060           0.295   
r2_o                0.004           0.042           0.082   
N                8835.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009           0.317          -0.025   
                  (0.154)         (0.228)         (0.069)   
wp_right2          -0.261           0.052           0.028   
                  (0.163)         (0.152)         (0.119)   
c.neg#c.wp~2       -0.308          -0.714           0.018   
                  (0.416)         (0.445)         (0.204)   
pho_order           0.004           0.001           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.040          -0.008          -0.027   
                  (0.058)         (0.041)         (0.041)   
age                -0.001          -0.000           0.001   
                  (0.002)         (0.004)         (0.001)   
income             -0.011          -0.028           0.021   
                  (0.167)         (0.106)         (0.087)   
university         -0.071           0.009           0.010   
                  (0.059)         (0.059)         (0.041)   
_cons               0.066          -0.039          -0.129   
                  (0.146)         (0.140)         (0.089)   
------------------------------------------------------------
r2_w                0.010           0.005           0.014   
r2_b                0.120           0.008           0.069   
r2_o                0.023           0.005           0.026   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.009          -0.039           0.026           0.171   
                  (0.140)         (0.158)         (0.177)         (0.146)   
wp_right2           0.109          -0.020           0.073           0.262   
                  (0.118)         (0.084)         (0.089)         (0.167)   
c.neg#c.wp~2        0.162           0.072          -0.013          -0.636   
                  (0.350)         (0.242)         (0.275)         (0.409)   
pho_order           0.008**         0.004*          0.002           0.003   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female              0.017           0.024           0.007           0.032   
                  (0.037)         (0.028)         (0.034)         (0.056)   
age                 0.002          -0.000          -0.002           0.003   
                  (0.002)         (0.001)         (0.002)         (0.007)   
income             -0.120          -0.011          -0.001           0.064   
                  (0.090)         (0.055)         (0.075)         (0.113)   
university          0.062          -0.025          -0.004          -0.039   
                  (0.037)         (0.030)         (0.040)         (0.079)   
_cons              -0.238*         -0.032          -0.014          -0.195   
                  (0.097)         (0.076)         (0.095)         (0.234)   
----------------------------------------------------------------------------
r2_w                0.022           0.006           0.003           0.012   
r2_b                0.306           0.062           0.035           0.147   
r2_o                0.038           0.012           0.005           0.023   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.270          -0.028           0.003   
                  (0.207)         (0.085)         (0.238)   
wp_right2          -0.103          -0.032          -0.158   
                  (0.160)         (0.093)         (0.210)   
c.neg#c.wp~2        0.357           0.169          -0.006   
                  (0.508)         (0.301)         (0.612)   
pho_order           0.012**         0.006**        -0.004   
                  (0.004)         (0.002)         (0.004)   
female             -0.124*         -0.069*         -0.081   
                  (0.062)         (0.029)         (0.064)   
age                 0.021          -0.005*         -0.018   
                  (0.016)         (0.002)         (0.021)   
income             -0.039           0.035           0.092   
                  (0.148)         (0.081)         (0.124)   
university          0.068          -0.011           0.017   
                  (0.166)         (0.044)         (0.099)   
_cons              -0.501           0.102           0.474   
                  (0.347)         (0.108)         (0.479)   
------------------------------------------------------------
r2_w                0.027           0.028           0.005   
r2_b                0.270           0.209           0.110   
r2_o                0.052           0.042           0.011   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3530&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.207           0.881***        0.018   
                  (0.120)         (0.169)         (0.104)   
wp_right2           0.023           0.151          -0.040   
                  (0.118)         (0.088)         (0.054)   
c.neg#c.wp~2       -0.378          -1.281***        0.004   
                  (0.317)         (0.277)         (0.166)   
pho_order           0.003           0.003           0.001   
                  (0.003)         (0.003)         (0.001)   
female              0.016          -0.070           0.034   
                  (0.048)         (0.036)         (0.018)   
age                 0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.017           0.045          -0.063   
                  (0.075)         (0.092)         (0.056)   
university          0.011          -0.069          -0.013   
                  (0.046)         (0.056)         (0.018)   
_cons              -0.128          -0.027           0.040   
                  (0.093)         (0.106)         (0.053)   
------------------------------------------------------------
r2_w                0.011           0.080           0.002   
r2_b                0.079           0.338           0.226   
r2_o                0.016           0.094           0.012   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.081          -0.011           0.025   
                  (0.092)         (0.128)         (0.108)   
wp_right2          -0.143           0.047           0.050   
                  (0.118)         (0.116)         (0.085)   
c.neg#c.wp~2       -0.181           0.009          -0.277   
                  (0.234)         (0.363)         (0.274)   
pho_order           0.001           0.004           0.003   
                  (0.002)         (0.003)         (0.002)   
female             -0.016           0.032          -0.001   
                  (0.054)         (0.041)         (0.028)   
age                 0.005*         -0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
income              0.131          -0.126           0.079   
                  (0.137)         (0.083)         (0.058)   
university         -0.035          -0.040           0.027   
                  (0.055)         (0.056)         (0.029)   
_cons              -0.283*          0.052          -0.127   
                  (0.117)         (0.090)         (0.068)   
------------------------------------------------------------
r2_w                0.004           0.003           0.004   
r2_b                0.278           0.117           0.029   
r2_o                0.059           0.011           0.006   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                 
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.182***        0.281           0.178   
                  (0.033)         (0.173)         (0.129)   
wp_right2           0.027          -0.042           0.098   
                  (0.022)         (0.133)         (0.154)   
c.neg#c.wp~2       -0.116          -0.183          -0.328   
                  (0.071)         (0.425)         (0.392)   
pho_order           0.004***        0.010**         0.009** 
                  (0.001)         (0.003)         (0.003)   
female             -0.002          -0.025           0.134   
                  (0.009)         (0.049)         (0.076)   
age                -0.000           0.001           0.001   
                  (0.000)         (0.005)         (0.003)   
income             -0.005          -0.080          -0.197   
                  (0.020)         (0.106)         (0.148)   
university          0.007           0.018           0.200*  
                  (0.010)         (0.049)         (0.079)   
_cons              -0.062**        -0.138          -0.298   
                  (0.022)         (0.143)         (0.163)   
------------------------------------------------------------
r2_w                0.012           0.055           0.030   
r2_b                0.010           0.059           0.342   
r2_o                0.012           0.055           0.078   
N                8834.000         360.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.138          -0.191           0.157*  
                  (0.161)         (0.251)         (0.075)   
wp_right2          -0.182           0.029           0.014   
                  (0.149)         (0.173)         (0.117)   
c.neg#c.wp~2        0.270           0.938          -0.086   
                  (0.437)         (0.491)         (0.221)   
pho_order           0.003           0.001           0.003   
                  (0.003)         (0.004)         (0.002)   
female              0.007           0.004          -0.045   
                  (0.053)         (0.047)         (0.040)   
age                -0.003          -0.001           0.000   
                  (0.002)         (0.004)         (0.001)   
income              0.195           0.070           0.021   
                  (0.152)         (0.121)         (0.085)   
university         -0.050          -0.011           0.014   
                  (0.054)         (0.068)         (0.040)   
_cons               0.058          -0.053          -0.095   
                  (0.136)         (0.160)         (0.088)   
------------------------------------------------------------
r2_w                0.021           0.035           0.041   
r2_b                0.191           0.022           0.086   
r2_o                0.033           0.034           0.049   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.321*          0.074           0.174           0.058   
                  (0.142)         (0.157)         (0.174)         (0.138)   
wp_right2           0.157          -0.015           0.098           0.289   
                  (0.120)         (0.095)         (0.088)         (0.208)   
c.neg#c.wp~2       -0.211          -0.026          -0.332          -0.126   
                  (0.356)         (0.241)         (0.269)         (0.385)   
pho_order           0.009***        0.003           0.002           0.002   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female             -0.006           0.017           0.013           0.029   
                  (0.038)         (0.032)         (0.034)         (0.071)   
age                 0.000          -0.002          -0.002           0.008   
                  (0.002)         (0.002)         (0.002)         (0.009)   
income             -0.104          -0.012          -0.019          -0.045   
                  (0.092)         (0.063)         (0.074)         (0.143)   
university          0.049          -0.010           0.035          -0.019   
                  (0.038)         (0.034)         (0.039)         (0.100)   
_cons              -0.206*          0.015          -0.031          -0.267   
                  (0.099)         (0.085)         (0.093)         (0.291)   
----------------------------------------------------------------------------
r2_w                0.049           0.009           0.006           0.001   
r2_b                0.232           0.033           0.049           0.156   
r2_o                0.057           0.012           0.009           0.022   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.209           0.163          -0.059   
                  (0.210)         (0.090)         (0.247)   
wp_right2          -0.101          -0.023          -0.105   
                  (0.159)         (0.099)         (0.218)   
c.neg#c.wp~2        0.244          -0.359           0.314   
                  (0.515)         (0.318)         (0.637)   
pho_order           0.010**         0.005**        -0.003   
                  (0.004)         (0.002)         (0.004)   
female             -0.126*         -0.067*         -0.063   
                  (0.061)         (0.031)         (0.066)   
age                 0.023          -0.004          -0.008   
                  (0.016)         (0.003)         (0.021)   
income             -0.046           0.033           0.119   
                  (0.147)         (0.086)         (0.128)   
university          0.151          -0.012          -0.096   
                  (0.165)         (0.047)         (0.103)   
_cons              -0.580           0.066           0.309   
                  (0.346)         (0.115)         (0.499)   
------------------------------------------------------------
r2_w                0.022           0.032           0.002   
r2_b                0.365           0.149           0.177   
r2_o                0.055           0.040           0.012   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6260&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.727***        0.590***        0.137   
                  (0.131)         (0.178)         (0.103)   
wp_right2           0.014           0.157          -0.036   
                  (0.128)         (0.093)         (0.054)   
c.neg#c.wp~2       -1.174***       -0.546          -0.163   
                  (0.344)         (0.293)         (0.165)   
pho_order           0.002           0.002           0.001   
                  (0.003)         (0.003)         (0.001)   
female              0.009          -0.057           0.026   
                  (0.052)         (0.038)         (0.018)   
age                 0.000          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.041           0.010          -0.046   
                  (0.082)         (0.097)         (0.056)   
university          0.034          -0.075          -0.006   
                  (0.050)         (0.059)         (0.018)   
_cons              -0.094           0.020           0.039   
                  (0.101)         (0.113)         (0.053)   
------------------------------------------------------------
r2_w                0.107           0.063           0.006   
r2_b                0.074           0.306           0.121   
r2_o                0.104           0.077           0.014   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.208*          0.087           0.142   
                  (0.106)         (0.131)         (0.107)   
wp_right2          -0.103           0.046           0.058   
                  (0.116)         (0.119)         (0.085)   
c.neg#c.wp~2        0.124          -0.133           0.061   
                  (0.268)         (0.372)         (0.272)   
pho_order           0.000           0.003           0.002   
                  (0.003)         (0.003)         (0.002)   
female              0.023           0.049           0.000   
                  (0.052)         (0.042)         (0.028)   
age                 0.004*         -0.001          -0.002   
                  (0.002)         (0.002)         (0.001)   
income              0.080          -0.129           0.107   
                  (0.134)         (0.085)         (0.059)   
university         -0.013          -0.044           0.027   
                  (0.053)         (0.058)         (0.029)   
_cons              -0.253*          0.046          -0.110   
                  (0.115)         (0.092)         (0.069)   
------------------------------------------------------------
r2_w                0.051           0.003           0.010   
r2_b                0.193           0.137           0.053   
r2_o                0.070           0.013           0.014   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                 
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.065*         -0.150           0.046   
                  (0.032)         (0.167)         (0.129)   
wp_right2           0.027          -0.070           0.081   
                  (0.021)         (0.129)         (0.138)   
c.neg#c.wp~2       -0.062           0.722          -0.127   
                  (0.070)         (0.406)         (0.390)   
pho_order           0.004***        0.010***        0.008*  
                  (0.001)         (0.003)         (0.004)   
female             -0.001           0.003           0.112   
                  (0.009)         (0.047)         (0.068)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.005)         (0.002)   
income             -0.001          -0.029          -0.083   
                  (0.019)         (0.103)         (0.132)   
university          0.006           0.022           0.130   
                  (0.009)         (0.048)         (0.071)   
_cons              -0.067**        -0.153          -0.263   
                  (0.022)         (0.138)         (0.148)   
------------------------------------------------------------
r2_w                0.004           0.050           0.021   
r2_b                0.011           0.021           0.219   
r2_o                0.005           0.048           0.043   
N                8835.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.164          -0.034           0.004   
                  (0.151)         (0.228)         (0.069)   
wp_right2          -0.259           0.059           0.005   
                  (0.140)         (0.152)         (0.127)   
c.neg#c.wp~2        0.399           0.121          -0.010   
                  (0.407)         (0.445)         (0.206)   
pho_order           0.005           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.042          -0.018          -0.042   
                  (0.049)         (0.041)         (0.044)   
age                -0.001          -0.003           0.001   
                  (0.002)         (0.004)         (0.001)   
income             -0.012          -0.002           0.047   
                  (0.142)         (0.106)         (0.093)   
university         -0.068           0.003           0.009   
                  (0.050)         (0.059)         (0.043)   
_cons               0.050           0.001          -0.133   
                  (0.128)         (0.140)         (0.095)   
------------------------------------------------------------
r2_w                0.012           0.001           0.014   
r2_b                0.126           0.016           0.080   
r2_o                0.022           0.002           0.030   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.181           0.184          -0.111          -0.030   
                  (0.139)         (0.156)         (0.168)         (0.134)   
wp_right2           0.131          -0.023           0.079           0.282   
                  (0.118)         (0.096)         (0.085)         (0.208)   
c.neg#c.wp~2       -0.114          -0.251           0.103           0.187   
                  (0.349)         (0.240)         (0.260)         (0.374)   
pho_order           0.007**         0.004*          0.003           0.003   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female              0.007           0.020           0.021           0.042   
                  (0.037)         (0.033)         (0.033)         (0.071)   
age                 0.001          -0.001          -0.001           0.008   
                  (0.002)         (0.002)         (0.002)         (0.009)   
income             -0.122           0.016           0.004          -0.001   
                  (0.090)         (0.064)         (0.071)         (0.142)   
university          0.058          -0.002           0.002          -0.047   
                  (0.037)         (0.034)         (0.038)         (0.100)   
_cons              -0.193*         -0.018          -0.056          -0.266   
                  (0.097)         (0.086)         (0.090)         (0.292)   
----------------------------------------------------------------------------
r2_w                0.023           0.011           0.006           0.005   
r2_b                0.222           0.049           0.044           0.183   
r2_o                0.034           0.016           0.008           0.031   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.067           0.011           0.330   
                  (0.212)         (0.092)         (0.237)   
wp_right2          -0.105          -0.009          -0.124   
                  (0.168)         (0.101)         (0.210)   
c.neg#c.wp~2       -0.530          -0.056          -0.608   
                  (0.525)         (0.325)         (0.612)   
pho_order           0.012**         0.005*         -0.003   
                  (0.004)         (0.002)         (0.004)   
female             -0.113          -0.047          -0.068   
                  (0.065)         (0.032)         (0.064)   
age                 0.021          -0.004          -0.014   
                  (0.016)         (0.003)         (0.021)   
income             -0.069           0.004           0.137   
                  (0.155)         (0.088)         (0.124)   
university          0.109           0.032          -0.029   
                  (0.174)         (0.048)         (0.100)   
_cons              -0.535           0.039           0.380   
                  (0.364)         (0.117)         (0.478)   
------------------------------------------------------------
r2_w                0.023           0.019           0.008   
r2_b                0.302           0.099           0.160   
r2_o                0.058           0.024           0.018   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_6510&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.305*          0.072          -0.198   
                  (0.119)         (0.161)         (0.102)   
wp_right2           0.026           0.148          -0.031   
                  (0.122)         (0.084)         (0.054)   
c.neg#c.wp~2       -0.664*         -0.155           0.320   
                  (0.313)         (0.264)         (0.164)   
pho_order           0.003           0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.020          -0.060           0.022   
                  (0.049)         (0.035)         (0.018)   
age                 0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.010           0.004          -0.031   
                  (0.078)         (0.088)         (0.055)   
university          0.007          -0.079           0.006   
                  (0.047)         (0.053)         (0.018)   
_cons              -0.138           0.018           0.020   
                  (0.095)         (0.101)         (0.052)   
------------------------------------------------------------
r2_w                0.021           0.001           0.009   
r2_b                0.075           0.315           0.110   
r2_o                0.026           0.025           0.012   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.143           0.044           0.071   
                  (0.094)         (0.129)         (0.110)   
wp_right2          -0.122           0.049           0.061   
                  (0.120)         (0.117)         (0.087)   
c.neg#c.wp~2       -0.075           0.149           0.027   
                  (0.239)         (0.366)         (0.279)   
pho_order           0.002           0.003           0.001   
                  (0.002)         (0.003)         (0.002)   
female             -0.001           0.029          -0.013   
                  (0.055)         (0.042)         (0.029)   
age                 0.004*         -0.002          -0.001   
                  (0.002)         (0.002)         (0.001)   
income              0.101          -0.133           0.095   
                  (0.140)         (0.083)         (0.060)   
university         -0.011          -0.027           0.042   
                  (0.056)         (0.057)         (0.030)   
_cons              -0.276*          0.060          -0.092   
                  (0.118)         (0.091)         (0.070)   
------------------------------------------------------------
r2_w                0.018           0.005           0.002   
r2_b                0.210           0.119           0.050   
r2_o                0.053           0.014           0.006   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                  
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.091**         0.151           0.018   
                  (0.033)         (0.167)         (0.132)   
wp_right2           0.027          -0.052           0.075   
                  (0.022)         (0.138)         (0.125)   
c.neg#c.wp~2       -0.013          -0.283           0.564   
                  (0.071)         (0.406)         (0.398)   
pho_order           0.003***        0.009**         0.008*  
                  (0.001)         (0.003)         (0.003)   
female              0.002          -0.011           0.106   
                  (0.009)         (0.051)         (0.061)   
age                -0.000          -0.001          -0.000   
                  (0.000)         (0.005)         (0.002)   
income             -0.006          -0.016          -0.144   
                  (0.020)         (0.111)         (0.118)   
university          0.005          -0.006           0.121   
                  (0.010)         (0.051)         (0.063)   
_cons              -0.052*         -0.097          -0.195   
                  (0.023)         (0.148)         (0.135)   
------------------------------------------------------------
r2_w                0.006           0.031           0.042   
r2_b                0.007           0.051           0.266   
r2_o                0.006           0.032           0.061   
N                8834.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.247          -0.334          -0.094   
                  (0.149)         (0.261)         (0.079)   
wp_right2          -0.263          -0.016           0.023   
                  (0.150)         (0.174)         (0.118)   
c.neg#c.wp~2       -0.562           0.956           0.674** 
                  (0.403)         (0.510)         (0.235)   
pho_order           0.005           0.001           0.005** 
                  (0.003)         (0.004)         (0.002)   
female              0.040           0.011          -0.026   
                  (0.053)         (0.047)         (0.040)   
age                -0.001          -0.002           0.000   
                  (0.002)         (0.004)         (0.001)   
income              0.023          -0.039           0.055   
                  (0.154)         (0.122)         (0.085)   
university         -0.077           0.054           0.007   
                  (0.054)         (0.068)         (0.040)   
_cons               0.071          -0.004          -0.136   
                  (0.135)         (0.160)         (0.088)   
------------------------------------------------------------
r2_w                0.016           0.013           0.059   
r2_b                0.169           0.044           0.110   
r2_o                0.032           0.016           0.068   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.220           0.121           0.221           0.223   
                  (0.140)         (0.156)         (0.171)         (0.139)   
wp_right2           0.140          -0.016           0.078           0.303   
                  (0.119)         (0.082)         (0.086)         (0.185)   
c.neg#c.wp~2       -0.261          -0.073          -0.307          -0.312   
                  (0.351)         (0.240)         (0.266)         (0.388)   
pho_order           0.005           0.003           0.002           0.003   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female             -0.001           0.016           0.015           0.054   
                  (0.037)         (0.027)         (0.033)         (0.063)   
age                 0.001          -0.001          -0.002           0.006   
                  (0.002)         (0.001)         (0.002)         (0.008)   
income             -0.087          -0.017          -0.013           0.083   
                  (0.091)         (0.054)         (0.072)         (0.126)   
university          0.047          -0.012           0.008          -0.026   
                  (0.037)         (0.029)         (0.038)         (0.088)   
_cons              -0.184           0.015          -0.023          -0.301   
                  (0.098)         (0.074)         (0.091)         (0.260)   
----------------------------------------------------------------------------
r2_w                0.016           0.009           0.006           0.019   
r2_b                0.181           0.043           0.039           0.175   
r2_o                0.025           0.012           0.007           0.036   
N                 561.000         660.000         527.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.251           0.140           0.386   
                  (0.207)         (0.088)         (0.265)   
wp_right2          -0.078          -0.028          -0.078   
                  (0.166)         (0.096)         (0.269)   
c.neg#c.wp~2        0.742          -0.198          -0.286   
                  (0.509)         (0.310)         (0.687)   
pho_order           0.011**         0.005**        -0.008   
                  (0.004)         (0.002)         (0.005)   
female             -0.110          -0.058          -0.064   
                  (0.064)         (0.030)         (0.083)   
age                 0.030          -0.004          -0.007   
                  (0.016)         (0.003)         (0.027)   
income              0.045           0.072           0.204   
                  (0.154)         (0.084)         (0.160)   
university          0.134           0.006          -0.185   
                  (0.173)         (0.045)         (0.129)   
_cons              -0.761*          0.043           0.382   
                  (0.363)         (0.111)         (0.618)   
------------------------------------------------------------
r2_w                0.021           0.028           0.025   
r2_b                0.285           0.178           0.165   
r2_o                0.052           0.039           0.041   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_3059&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.271*          0.042          -0.141   
                  (0.123)         (0.174)         (0.105)   
wp_right2           0.008           0.151          -0.028   
                  (0.121)         (0.090)         (0.055)   
c.neg#c.wp~2       -0.518           0.124           0.304   
                  (0.325)         (0.287)         (0.169)   
pho_order           0.002          -0.002           0.001   
                  (0.003)         (0.003)         (0.001)   
female              0.016          -0.042           0.020   
                  (0.049)         (0.037)         (0.019)   
age                 0.001          -0.002           0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.071          -0.058          -0.045   
                  (0.077)         (0.095)         (0.057)   
university          0.012          -0.086           0.003   
                  (0.047)         (0.057)         (0.019)   
_cons              -0.077           0.084           0.013   
                  (0.095)         (0.110)         (0.054)   
------------------------------------------------------------
r2_w                0.015           0.013           0.011   
r2_b                0.088           0.248           0.068   
r2_o                0.022           0.030           0.014   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.094           0.201          -0.072   
                  (0.093)         (0.131)         (0.108)   
wp_right2          -0.115           0.056           0.058   
                  (0.118)         (0.119)         (0.085)   
c.neg#c.wp~2        0.005          -0.634           0.353   
                  (0.235)         (0.372)         (0.274)   
pho_order           0.002           0.003           0.002   
                  (0.002)         (0.003)         (0.002)   
female             -0.008           0.046           0.010   
                  (0.053)         (0.042)         (0.028)   
age                 0.004          -0.002          -0.001   
                  (0.002)         (0.002)         (0.001)   
income              0.062          -0.119           0.098   
                  (0.137)         (0.085)         (0.059)   
university          0.006          -0.055           0.035   
                  (0.055)         (0.058)         (0.029)   
_cons              -0.250*          0.074          -0.128   
                  (0.116)         (0.092)         (0.069)   
------------------------------------------------------------
r2_w                0.012           0.007           0.003   
r2_b                0.180           0.148           0.042   
r2_o                0.042           0.019           0.006   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.          
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.041           0.410*          0.024   
                  (0.032)         (0.169)         (0.124)   
wp_right2           0.026          -0.065           0.083   
                  (0.021)         (0.131)         (0.149)   
c.neg#c.wp~2       -0.066          -0.962*         -0.044   
                  (0.070)         (0.412)         (0.374)   
pho_order           0.004***        0.009**         0.007*  
                  (0.001)         (0.003)         (0.003)   
female              0.000           0.004           0.111   
                  (0.009)         (0.048)         (0.074)   
age                -0.000          -0.004           0.000   
                  (0.000)         (0.005)         (0.003)   
income             -0.015          -0.056          -0.070   
                  (0.019)         (0.104)         (0.143)   
university          0.008           0.037           0.157*  
                  (0.009)         (0.048)         (0.077)   
_cons              -0.064**        -0.047          -0.273   
                  (0.022)         (0.140)         (0.158)   
------------------------------------------------------------
r2_w                0.004           0.043           0.015   
r2_b                0.008           0.156           0.253   
r2_o                0.004           0.050           0.049   
N                8835.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.077          -0.028           0.063   
                  (0.149)         (0.236)         (0.073)   
wp_right2          -0.268           0.008           0.017   
                  (0.152)         (0.157)         (0.125)   
c.neg#c.wp~2        0.218           0.210          -0.178   
                  (0.402)         (0.461)         (0.215)   
pho_order           0.004           0.001           0.004*  
                  (0.003)         (0.003)         (0.002)   
female              0.047           0.002          -0.044   
                  (0.054)         (0.042)         (0.043)   
age                -0.001          -0.002           0.001   
                  (0.002)         (0.004)         (0.001)   
income              0.023           0.049          -0.019   
                  (0.156)         (0.110)         (0.091)   
university         -0.088           0.019           0.009   
                  (0.055)         (0.061)         (0.042)   
_cons               0.063          -0.032          -0.095   
                  (0.138)         (0.144)         (0.093)   
------------------------------------------------------------
r2_w                0.008           0.003           0.017   
r2_b                0.141           0.023           0.081   
r2_o                0.022           0.005           0.031   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.184           0.108          -0.163           0.017   
                  (0.139)         (0.152)         (0.170)         (0.135)   
wp_right2           0.099          -0.023           0.072           0.340   
                  (0.118)         (0.085)         (0.086)         (0.200)   
c.neg#c.wp~2       -0.381          -0.116           0.166          -0.095   
                  (0.349)         (0.234)         (0.263)         (0.379)   
pho_order           0.008***        0.004*          0.002           0.004   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female              0.002           0.016           0.022           0.023   
                  (0.037)         (0.029)         (0.033)         (0.068)   
age                 0.002          -0.002          -0.002           0.010   
                  (0.002)         (0.001)         (0.002)         (0.009)   
income             -0.129          -0.004          -0.024           0.048   
                  (0.090)         (0.056)         (0.072)         (0.138)   
university          0.056           0.002           0.006          -0.060   
                  (0.037)         (0.030)         (0.038)         (0.096)   
_cons              -0.229*          0.001          -0.022          -0.360   
                  (0.097)         (0.076)         (0.091)         (0.282)   
----------------------------------------------------------------------------
r2_w                0.024           0.010           0.006           0.006   
r2_b                0.214           0.040           0.068           0.182   
r2_o                0.037           0.013           0.010           0.029   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.079          -0.100           0.221   
                  (0.211)         (0.087)         (0.249)   
wp_right2          -0.114          -0.024          -0.146   
                  (0.161)         (0.095)         (0.221)   
c.neg#c.wp~2        0.392           0.316          -0.118   
                  (0.520)         (0.307)         (0.645)   
pho_order           0.011**         0.006**        -0.003   
                  (0.004)         (0.002)         (0.004)   
female             -0.113          -0.054          -0.096   
                  (0.062)         (0.030)         (0.067)   
age                 0.022          -0.004          -0.019   
                  (0.016)         (0.002)         (0.022)   
income             -0.108           0.078           0.171   
                  (0.148)         (0.083)         (0.131)   
university          0.100           0.023          -0.093   
                  (0.167)         (0.045)         (0.105)   
_cons              -0.502          -0.008           0.542   
                  (0.351)         (0.110)         (0.508)   
------------------------------------------------------------
r2_w                0.017           0.028           0.009   
r2_b                0.308           0.199           0.201   
r2_o                0.048           0.038           0.026   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_7380&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.145           0.016           0.097   
                  (0.116)         (0.160)         (0.101)   
wp_right2           0.007           0.146          -0.036   
                  (0.114)         (0.083)         (0.053)   
c.neg#c.wp~2       -0.331          -0.079          -0.138   
                  (0.305)         (0.262)         (0.162)   
pho_order           0.003           0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.015          -0.049           0.024   
                  (0.046)         (0.034)         (0.018)   
age                 0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.032          -0.021          -0.048   
                  (0.072)         (0.087)         (0.055)   
university          0.016          -0.089          -0.009   
                  (0.044)         (0.053)         (0.018)   
_cons              -0.135           0.037           0.034   
                  (0.090)         (0.100)         (0.052)   
------------------------------------------------------------
r2_w                0.006           0.001           0.003   
r2_b                0.110           0.307           0.178   
r2_o                0.015           0.024           0.010   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.027           0.010           0.075   
                  (0.098)         (0.134)         (0.108)   
wp_right2          -0.109           0.024           0.060   
                  (0.108)         (0.122)         (0.086)   
c.neg#c.wp~2        0.238          -0.322          -0.255   
                  (0.248)         (0.381)         (0.274)   
pho_order           0.002           0.004           0.003   
                  (0.002)         (0.003)         (0.002)   
female             -0.005           0.031           0.013   
                  (0.049)         (0.043)         (0.028)   
age                 0.004          -0.001          -0.001   
                  (0.002)         (0.002)         (0.001)   
income              0.082          -0.094           0.077   
                  (0.124)         (0.087)         (0.059)   
university         -0.008          -0.011           0.034   
                  (0.050)         (0.059)         (0.030)   
_cons              -0.243*          0.002          -0.131   
                  (0.107)         (0.095)         (0.069)   
------------------------------------------------------------
r2_w                0.006           0.007           0.002   
r2_b                0.194           0.090           0.028   
r2_o                0.033           0.012           0.004   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.          
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.006          -0.005          -0.025   
                  (0.032)         (0.171)         (0.128)   
wp_right2           0.026          -0.056           0.076   
                  (0.022)         (0.127)         (0.141)   
c.neg#c.wp~2       -0.054          -0.011          -0.183   
                  (0.070)         (0.430)         (0.387)   
pho_order           0.004***        0.011***        0.008*  
                  (0.001)         (0.003)         (0.003)   
female             -0.002           0.001           0.097   
                  (0.009)         (0.047)         (0.070)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.005)         (0.002)   
income              0.000          -0.026          -0.066   
                  (0.020)         (0.101)         (0.135)   
university          0.005          -0.010           0.161*  
                  (0.010)         (0.047)         (0.072)   
_cons              -0.074***       -0.159          -0.301*  
                  (0.022)         (0.137)         (0.151)   
------------------------------------------------------------
r2_w                0.005           0.039           0.023   
r2_b                0.009           0.045           0.263   
r2_o                0.005           0.040           0.052   
N                8834.000         360.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.166          -0.096           0.085   
                  (0.149)         (0.230)         (0.080)   
wp_right2          -0.262           0.091          -0.033   
                  (0.173)         (0.163)         (0.128)   
c.neg#c.wp~2        0.390           0.025          -0.415   
                  (0.404)         (0.450)         (0.236)   
pho_order           0.006*          0.003           0.006***
                  (0.003)         (0.003)         (0.002)   
female              0.069          -0.028          -0.061   
                  (0.062)         (0.044)         (0.044)   
age                -0.000          -0.002           0.001   
                  (0.003)         (0.004)         (0.001)   
income              0.021          -0.049           0.080   
                  (0.178)         (0.115)         (0.093)   
university         -0.067          -0.003          -0.004   
                  (0.063)         (0.064)         (0.043)   
_cons              -0.002          -0.019          -0.151   
                  (0.154)         (0.150)         (0.096)   
------------------------------------------------------------
r2_w                0.015           0.005           0.046   
r2_b                0.110           0.017           0.130   
r2_o                0.027           0.006           0.063   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.120          -0.011           0.213           0.057   
                  (0.141)         (0.153)         (0.168)         (0.132)   
wp_right2           0.155          -0.022           0.073           0.334   
                  (0.119)         (0.086)         (0.085)         (0.208)   
c.neg#c.wp~2       -0.189           0.065          -0.490          -0.478   
                  (0.353)         (0.235)         (0.260)         (0.369)   
pho_order           0.008**         0.003           0.002           0.003   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female             -0.022           0.023           0.008           0.040   
                  (0.038)         (0.029)         (0.033)         (0.071)   
age                 0.002          -0.001          -0.001           0.009   
                  (0.002)         (0.001)         (0.002)         (0.009)   
income             -0.012          -0.011          -0.028           0.055   
                  (0.091)         (0.057)         (0.071)         (0.143)   
university          0.043          -0.002           0.005          -0.039   
                  (0.038)         (0.030)         (0.038)         (0.100)   
_cons              -0.276**         0.006          -0.031          -0.355   
                  (0.098)         (0.077)         (0.090)         (0.294)   
----------------------------------------------------------------------------
r2_w                0.017           0.006           0.015           0.016   
r2_b                0.192           0.039           0.011           0.137   
r2_o                0.027           0.009           0.015           0.033   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.143           0.084           0.388   
                  (0.204)         (0.087)         (0.253)   
wp_right2          -0.090          -0.027          -0.131   
                  (0.166)         (0.094)         (0.225)   
c.neg#c.wp~2        0.266          -0.610*         -0.729   
                  (0.502)         (0.306)         (0.654)   
pho_order           0.012**         0.006**        -0.005   
                  (0.004)         (0.002)         (0.004)   
female             -0.108          -0.058*         -0.049   
                  (0.064)         (0.030)         (0.068)   
age                 0.027          -0.005          -0.018   
                  (0.016)         (0.002)         (0.022)   
income             -0.006           0.063           0.135   
                  (0.154)         (0.082)         (0.132)   
university          0.102           0.017           0.016   
                  (0.173)         (0.045)         (0.106)   
_cons              -0.667           0.033           0.447   
                  (0.362)         (0.110)         (0.513)   
------------------------------------------------------------
r2_w                0.023           0.046           0.013   
r2_b                0.270           0.165           0.101   
r2_o                0.052           0.054           0.017   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9300&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.119           0.061          -0.128   
                  (0.114)         (0.167)         (0.101)   
wp_right2          -0.001           0.155          -0.032   
                  (0.132)         (0.086)         (0.053)   
c.neg#c.wp~2        0.208          -0.064           0.185   
                  (0.302)         (0.274)         (0.162)   
pho_order           0.002           0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.017          -0.065           0.015   
                  (0.053)         (0.036)         (0.018)   
age                 0.002          -0.002          -0.001   
                  (0.001)         (0.002)         (0.001)   
income             -0.040          -0.022          -0.044   
                  (0.084)         (0.091)         (0.055)   
university          0.035          -0.079          -0.007   
                  (0.051)         (0.055)         (0.018)   
_cons              -0.145           0.033           0.039   
                  (0.102)         (0.104)         (0.052)   
------------------------------------------------------------
r2_w                0.004           0.001           0.005   
r2_b                0.117           0.296           0.125   
r2_o                0.019           0.026           0.009   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.039          -0.166           0.049   
                  (0.092)         (0.129)         (0.107)   
wp_right2          -0.121           0.032           0.046   
                  (0.117)         (0.117)         (0.087)   
c.neg#c.wp~2       -0.057           0.165          -0.272   
                  (0.235)         (0.365)         (0.272)   
pho_order           0.002           0.003           0.002   
                  (0.002)         (0.003)         (0.002)   
female              0.002           0.045          -0.010   
                  (0.053)         (0.042)         (0.029)   
age                 0.004*         -0.001          -0.001   
                  (0.002)         (0.002)         (0.001)   
income              0.107          -0.092           0.107   
                  (0.136)         (0.083)         (0.060)   
university         -0.038          -0.045           0.033   
                  (0.054)         (0.057)         (0.030)   
_cons              -0.276*          0.026          -0.126   
                  (0.115)         (0.090)         (0.069)   
------------------------------------------------------------
r2_w                0.004           0.009           0.003   
r2_b                0.222           0.083           0.032   
r2_o                0.044           0.015           0.005   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.          
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negative
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; | p_negative==0) ,
&gt;  re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot;
&gt;  | p_negative==0) , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.071*          0.276           0.023   
                  (0.032)         (0.165)         (0.124)   
wp_right2           0.024          -0.052           0.082   
                  (0.021)         (0.127)         (0.134)   
c.neg#c.wp~2       -0.062          -0.656          -0.181   
                  (0.070)         (0.402)         (0.374)   
pho_order           0.003***        0.011***        0.007*  
                  (0.001)         (0.003)         (0.003)   
female              0.003           0.000           0.113   
                  (0.009)         (0.047)         (0.066)   
age                -0.000          -0.001           0.001   
                  (0.000)         (0.005)         (0.002)   
income             -0.013          -0.045          -0.086   
                  (0.019)         (0.102)         (0.128)   
university          0.002          -0.005           0.147*  
                  (0.009)         (0.047)         (0.068)   
_cons              -0.066**        -0.124          -0.275   
                  (0.022)         (0.137)         (0.141)   
------------------------------------------------------------
r2_w                0.004           0.047           0.017   
r2_b                0.009           0.079           0.291   
r2_o                0.005           0.049           0.050   
N                8835.000         361.000         297.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.207          -0.037           0.146*  
                  (0.161)         (0.224)         (0.072)   
wp_right2          -0.206           0.017           0.023   
                  (0.148)         (0.168)         (0.106)   
c.neg#c.wp~2        0.933*          0.061          -0.287   
                  (0.435)         (0.438)         (0.215)   
pho_order           0.003           0.002           0.004** 
                  (0.003)         (0.003)         (0.002)   
female              0.026          -0.013          -0.027   
                  (0.053)         (0.045)         (0.036)   
age                -0.001          -0.000           0.000   
                  (0.002)         (0.004)         (0.001)   
income              0.080           0.053           0.062   
                  (0.151)         (0.118)         (0.077)   
university         -0.046           0.039           0.016   
                  (0.053)         (0.066)         (0.036)   
_cons               0.046          -0.095          -0.147   
                  (0.134)         (0.153)         (0.080)   
------------------------------------------------------------
r2_w                0.016           0.001           0.029   
r2_b                0.094           0.023           0.079   
r2_o                0.021           0.003           0.037   
N                 396.000         605.000         385.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot;
&gt;  | p_negative==0) , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot;
&gt;  | p_negative==0) , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.220          -0.052          -0.075           0.144   
                  (0.136)         (0.154)         (0.176)         (0.137)   
wp_right2           0.115          -0.028           0.076           0.333   
                  (0.115)         (0.090)         (0.089)         (0.189)   
c.neg#c.wp~2       -0.320           0.089           0.213          -0.246   
                  (0.339)         (0.236)         (0.272)         (0.383)   
pho_order           0.008**         0.003           0.002           0.004   
                  (0.003)         (0.002)         (0.002)         (0.003)   
female             -0.011           0.028           0.040           0.024   
                  (0.036)         (0.030)         (0.034)         (0.064)   
age                 0.002          -0.000          -0.003           0.008   
                  (0.002)         (0.001)         (0.002)         (0.008)   
income             -0.097          -0.017          -0.014           0.073   
                  (0.088)         (0.059)         (0.075)         (0.130)   
university          0.061          -0.010           0.012          -0.028   
                  (0.036)         (0.032)         (0.040)         (0.091)   
_cons              -0.234*         -0.024          -0.004          -0.349   
                  (0.095)         (0.080)         (0.094)         (0.267)   
----------------------------------------------------------------------------
r2_w                0.027           0.004           0.005           0.012   
r2_b                0.247           0.035           0.115           0.159   
r2_o                0.039           0.008           0.011           0.029   
N                 561.000         660.000         528.000         264.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.192           0.041          -0.228   
                  (0.213)         (0.088)         (0.235)   
wp_right2          -0.100          -0.014          -0.152   
                  (0.162)         (0.096)         (0.208)   
c.neg#c.wp~2       -0.448           0.159           0.506   
                  (0.524)         (0.310)         (0.607)   
pho_order           0.011**         0.006**        -0.004   
                  (0.004)         (0.002)         (0.004)   
female             -0.115          -0.049          -0.083   
                  (0.062)         (0.030)         (0.063)   
age                 0.032*         -0.003          -0.023   
                  (0.016)         (0.003)         (0.021)   
income             -0.069           0.001           0.175   
                  (0.150)         (0.084)         (0.123)   
university          0.040           0.003          -0.057   
                  (0.168)         (0.045)         (0.099)   
_cons              -0.653           0.043           0.601   
                  (0.353)         (0.111)         (0.476)   
------------------------------------------------------------
r2_w                0.019           0.035           0.006   
r2_b                0.336           0.076           0.208   
r2_o                0.054           0.038           0.021   
N                 341.000         407.000         396.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; (stimulus==&quot;p_9325&quot; |
&gt;  p_negative==0) , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.188           0.216          -0.130   
                  (0.121)         (0.181)         (0.104)   
wp_right2           0.036           0.162          -0.033   
                  (0.119)         (0.094)         (0.054)   
c.neg#c.wp~2       -0.243          -0.123           0.187   
                  (0.319)         (0.298)         (0.166)   
pho_order           0.003           0.001          -0.000   
                  (0.003)         (0.003)         (0.001)   
female              0.036          -0.057           0.014   
                  (0.048)         (0.039)         (0.019)   
age                 0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.050          -0.070          -0.049   
                  (0.075)         (0.098)         (0.056)   
university         -0.002          -0.071          -0.009   
                  (0.046)         (0.059)         (0.018)   
_cons              -0.114           0.045           0.055   
                  (0.093)         (0.113)         (0.053)   
------------------------------------------------------------
r2_w                0.013           0.016           0.003   
r2_b                0.112           0.315           0.067   
r2_o                0.021           0.035           0.006   
N                 352.000         352.000         528.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.164           0.210           0.157   
                  (0.099)         (0.133)         (0.108)   
wp_right2          -0.104           0.058           0.037   
                  (0.116)         (0.131)         (0.086)   
c.neg#c.wp~2        0.648*         -0.283          -0.352   
                  (0.253)         (0.378)         (0.275)   
pho_order          -0.000           0.003           0.003   
                  (0.002)         (0.003)         (0.002)   
female              0.001           0.062           0.006   
                  (0.053)         (0.047)         (0.029)   
age                 0.004*         -0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
income             -0.011          -0.154           0.111   
                  (0.135)         (0.094)         (0.059)   
university          0.029          -0.073           0.011   
                  (0.054)         (0.064)         (0.030)   
_cons              -0.201           0.063          -0.144*  
                  (0.115)         (0.100)         (0.069)   
------------------------------------------------------------
r2_w                0.023           0.009           0.003   
r2_b                0.178           0.141           0.031   
r2_o                0.046           0.023           0.005   
N                 339.000         523.000        1529.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.                  
. * Table A6 Row 2
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(56,936 real changes made, 17,708 to missing)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.017          -0.036          -0.112          -0.078   
                  (0.022)         (0.139)         (0.101)         (0.061)   
wp_right2           0.063          -0.275          -0.112          -0.268   
                  (0.052)         (0.325)         (0.571)         (0.203)   
c.neg#c.wp~2        0.045           0.140           0.731*          0.134   
                  (0.048)         (0.338)         (0.341)         (0.188)   
vid_order          -0.074***       -0.071*         -0.122***       -0.042*  
                  (0.005)         (0.030)         (0.030)         (0.019)   
female             -0.027          -0.083           0.188          -0.013   
                  (0.023)         (0.122)         (0.249)         (0.101)   
age                 0.001           0.013           0.025          -0.002   
                  (0.001)         (0.012)         (0.025)         (0.003)   
income              0.016           0.021          -0.201           0.050   
                  (0.049)         (0.281)         (0.443)         (0.197)   
university         -0.021          -0.016          -0.167          -0.061   
                  (0.025)         (0.129)         (0.336)         (0.105)   
_cons               0.215***        0.097          -0.176           0.326   
                  (0.055)         (0.349)         (0.779)         (0.228)   
----------------------------------------------------------------------------
r2_w                0.050           0.048           0.152           0.059   
r2_b                0.037           0.121           0.085           0.077   
r2_o                0.046           0.057           0.129           0.063   
N                4665.000         175.000         160.000         135.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.104          -0.086          -0.082   
                  (0.120)         (0.186)         (0.082)   
wp_right2           0.445          -0.112           0.067   
                  (0.481)         (0.383)         (0.252)   
c.neg#c.wp~2       -0.110           0.224           0.342   
                  (0.329)         (0.361)         (0.239)   
vid_order          -0.108***       -0.111***       -0.041*  
                  (0.029)         (0.023)         (0.019)   
female              0.170           0.006          -0.008   
                  (0.172)         (0.105)         (0.086)   
age                 0.005          -0.011           0.001   
                  (0.007)         (0.010)         (0.003)   
income              0.100           0.429           0.252   
                  (0.497)         (0.257)         (0.184)   
university          0.229          -0.133          -0.009   
                  (0.176)         (0.153)         (0.085)   
_cons              -0.341           0.668          -0.044   
                  (0.426)         (0.355)         (0.200)   
------------------------------------------------------------
r2_w                0.099           0.094           0.042   
r2_b                0.129           0.130           0.163   
r2_o                0.108           0.099           0.057   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.068           0.153           0.109   
                  (0.125)         (0.097)         (0.110)   
wp_right2          -0.090          -0.077          -0.236   
                  (0.394)         (0.161)         (0.209)   
c.neg#c.wp~2        0.077          -0.205          -0.176   
                  (0.311)         (0.149)         (0.172)   
vid_order          -0.119***       -0.067***       -0.087***
                  (0.026)         (0.012)         (0.018)   
female             -0.106          -0.124*         -0.110   
                  (0.128)         (0.055)         (0.084)   
age                -0.003           0.001           0.002   
                  (0.007)         (0.003)         (0.006)   
income              0.029           0.156           0.117   
                  (0.310)         (0.108)         (0.176)   
university         -0.077          -0.033          -0.101   
                  (0.129)         (0.057)         (0.098)   
_cons               0.708*          0.243           0.363   
                  (0.332)         (0.145)         (0.219)   
------------------------------------------------------------
r2_w                0.106           0.109           0.101   
r2_b                0.055           0.202           0.185   
r2_o                0.095           0.131           0.120   
N                 255.000         300.000         250.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.071           0.006           0.040   
                  (0.088)         (0.161)         (0.057)   
wp_right2           0.241          -0.379           0.070   
                  (0.406)         (0.391)         (0.251)   
c.neg#c.wp~2        0.220           0.194          -0.049   
                  (0.309)         (0.402)         (0.200)   
vid_order          -0.133***       -0.048          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.100           0.112          -0.178*  
                  (0.132)         (0.152)         (0.082)   
age                -0.011           0.010           0.001   
                  (0.023)         (0.039)         (0.007)   
income             -0.392          -0.043           0.451*  
                  (0.300)         (0.377)         (0.228)   
university         -0.254          -0.100           0.167   
                  (0.188)         (0.292)         (0.124)   
_cons               1.094           0.098          -0.090   
                  (0.684)         (0.867)         (0.304)   
------------------------------------------------------------
r2_w                0.075           0.016           0.101   
r2_b                0.154           0.163           0.205   
r2_o                0.095           0.035           0.129   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.063          -0.060           0.082          -0.097   
                  (0.170)         (0.080)         (0.152)         (0.069)   
wp_right2           0.139           0.236           0.283           0.017   
                  (0.484)         (0.246)         (0.252)         (0.137)   
c.neg#c.wp~2       -0.004           0.208          -0.067           0.160   
                  (0.445)         (0.211)         (0.252)         (0.112)   
vid_order          -0.099**        -0.087***       -0.062*         -0.020*  
                  (0.034)         (0.021)         (0.026)         (0.009)   
female              0.073          -0.090           0.110          -0.008   
                  (0.150)         (0.102)         (0.104)         (0.048)   
age                -0.046          -0.004           0.005           0.003   
                  (0.049)         (0.002)         (0.005)         (0.002)   
income             -0.389           0.094          -0.058           0.210   
                  (0.291)         (0.160)         (0.263)         (0.146)   
university         -0.055           0.012          -0.075           0.015   
                  (0.233)         (0.098)         (0.159)         (0.048)   
_cons               1.526           0.390*         -0.066          -0.091   
                  (1.120)         (0.195)         (0.311)         (0.134)   
----------------------------------------------------------------------------
r2_w                0.052           0.108           0.042           0.023   
r2_b                0.189           0.331           0.225           0.112   
r2_o                0.075           0.144           0.073           0.044   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.101          -0.012           0.051   
                  (0.068)         (0.082)         (0.056)   
wp_right2           0.108           0.012           0.125   
                  (0.184)         (0.302)         (0.157)   
c.neg#c.wp~2        0.198           0.274           0.005   
                  (0.173)         (0.235)         (0.132)   
vid_order          -0.025          -0.077***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.094          -0.097          -0.033   
                  (0.085)         (0.110)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.425          -0.094          -0.010   
                  (0.217)         (0.220)         (0.120)   
university          0.051          -0.054           0.078   
                  (0.087)         (0.149)         (0.062)   
_cons               0.161           0.480*         -0.006   
                  (0.195)         (0.225)         (0.141)   
------------------------------------------------------------
r2_w                0.028           0.086           0.020   
r2_b                0.219           0.058           0.026   
r2_o                0.068           0.078           0.022   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.034*          0.038           0.017          -0.036   
                  (0.013)         (0.073)         (0.070)         (0.043)   
wp_right2_~2        0.016           0.004          -0.884*         -0.078   
                  (0.025)         (0.134)         (0.350)         (0.110)   
c.neg#c.wp~2        0.002          -0.071           0.503*         -0.055   
                  (0.023)         (0.134)         (0.221)         (0.104)   
vid_order          -0.074***       -0.071*         -0.114***       -0.040*  
                  (0.005)         (0.030)         (0.031)         (0.019)   
female             -0.027          -0.090          -0.163           0.006   
                  (0.023)         (0.123)         (0.248)         (0.099)   
age                 0.001           0.014           0.012          -0.002   
                  (0.001)         (0.011)         (0.021)         (0.004)   
income              0.015           0.010          -0.106           0.020   
                  (0.049)         (0.285)         (0.369)         (0.202)   
university         -0.024          -0.032           0.032          -0.043   
                  (0.024)         (0.128)         (0.280)         (0.106)   
_cons               0.236***       -0.005           0.182           0.243   
                  (0.052)         (0.327)         (0.640)         (0.223)   
----------------------------------------------------------------------------
r2_w                0.050           0.050           0.142           0.061   
r2_b                0.036           0.089           0.234           0.032   
r2_o                0.045           0.055           0.174           0.054   
N                4665.000         175.000         160.000         135.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.104          -0.018          -0.003   
                  (0.069)         (0.086)         (0.046)   
wp_right2_~2        0.038          -0.088          -0.042   
                  (0.223)         (0.103)         (0.103)   
c.neg#c.wp~2       -0.157           0.064           0.109   
                  (0.158)         (0.104)         (0.102)   
vid_order          -0.109***       -0.110***       -0.040*  
                  (0.028)         (0.023)         (0.019)   
female              0.196           0.014          -0.030   
                  (0.174)         (0.100)         (0.082)   
age                 0.005          -0.011           0.000   
                  (0.007)         (0.010)         (0.003)   
income             -0.034           0.451           0.293   
                  (0.479)         (0.257)         (0.185)   
university          0.191          -0.124          -0.008   
                  (0.178)         (0.150)         (0.085)   
_cons              -0.128           0.652          -0.030   
                  (0.356)         (0.339)         (0.186)   
------------------------------------------------------------
r2_w                0.106           0.093           0.039   
r2_b                0.101           0.146           0.132   
r2_o                0.104           0.101           0.051   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.095           0.191*          0.056   
                  (0.064)         (0.081)         (0.073)   
wp_right2_~2        0.009          -0.112          -0.031   
                  (0.190)         (0.092)         (0.100)   
c.neg#c.wp~2        0.001          -0.186*         -0.073   
                  (0.137)         (0.085)         (0.085)   
vid_order          -0.120***       -0.067***       -0.088***
                  (0.027)         (0.012)         (0.018)   
female             -0.107          -0.116*         -0.123   
                  (0.128)         (0.054)         (0.086)   
age                -0.004           0.001           0.001   
                  (0.007)         (0.003)         (0.006)   
income              0.044           0.162           0.164   
                  (0.320)         (0.105)         (0.176)   
university         -0.078          -0.016          -0.070   
                  (0.127)         (0.057)         (0.098)   
_cons               0.685*          0.292*          0.243   
                  (0.316)         (0.140)         (0.191)   
------------------------------------------------------------
r2_w                0.106           0.120           0.100   
r2_b                0.055           0.242           0.155   
r2_o                0.094           0.149           0.111   
N                 255.000         300.000         250.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.029           0.060           0.024   
                  (0.058)         (0.085)         (0.030)   
wp_right2_~2       -0.192          -0.083          -0.166   
                  (0.249)         (0.171)         (0.166)   
c.neg#c.wp~2        0.105           0.062           0.056   
                  (0.191)         (0.168)         (0.126)   
vid_order          -0.133***       -0.050          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.147           0.090          -0.187*  
                  (0.135)         (0.151)         (0.081)   
age                -0.025           0.014           0.000   
                  (0.024)         (0.040)         (0.007)   
income             -0.501           0.007           0.486*  
                  (0.302)         (0.375)         (0.225)   
university         -0.263          -0.085           0.120   
                  (0.187)         (0.296)         (0.128)   
_cons               1.584*         -0.118          -0.003   
                  (0.642)         (0.842)         (0.291)   
------------------------------------------------------------
r2_w                0.074           0.015           0.102   
r2_b                0.152           0.143           0.226   
r2_o                0.095           0.030           0.135   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2_dicho2 vid_order female age income u
&gt; niversity if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.046          -0.020           0.056          -0.066   
                  (0.078)         (0.049)         (0.101)         (0.041)   
wp_right2_~2       -0.042           0.152           0.187          -0.028   
                  (0.197)         (0.109)         (0.125)         (0.054)   
c.neg#c.wp~2        0.105           0.110          -0.017           0.085   
                  (0.184)         (0.098)         (0.119)         (0.047)   
vid_order          -0.099**        -0.086***       -0.064*         -0.020*  
                  (0.034)         (0.021)         (0.026)         (0.010)   
female              0.060          -0.077           0.094          -0.002   
                  (0.144)         (0.098)         (0.105)         (0.046)   
age                -0.051          -0.003           0.005           0.003   
                  (0.047)         (0.002)         (0.005)         (0.002)   
income             -0.408           0.085          -0.112           0.230   
                  (0.285)         (0.154)         (0.266)         (0.137)   
university         -0.041          -0.021          -0.038           0.007   
                  (0.240)         (0.102)         (0.161)         (0.048)   
_cons               1.698           0.429*         -0.024          -0.069   
                  (0.998)         (0.174)         (0.296)         (0.125)   
----------------------------------------------------------------------------
r2_w                0.054           0.107           0.042           0.027   
r2_b                0.189           0.372           0.261           0.123   
r2_o                0.076           0.151           0.079           0.049   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.071           0.072           0.054   
                  (0.047)         (0.047)         (0.029)   
wp_right2_~2        0.031           0.046           0.097   
                  (0.095)         (0.146)         (0.066)   
c.neg#c.wp~2        0.130          -0.017          -0.006   
                  (0.092)         (0.118)         (0.057)   
vid_order          -0.025          -0.076***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.093          -0.090          -0.028   
                  (0.086)         (0.111)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.399          -0.084          -0.015   
                  (0.222)         (0.217)         (0.119)   
university          0.045          -0.064           0.078   
                  (0.087)         (0.151)         (0.061)   
_cons               0.154           0.468*          0.019   
                  (0.196)         (0.226)         (0.132)   
------------------------------------------------------------
r2_w                0.031           0.078           0.020   
r2_b                0.220           0.065           0.034   
r2_o                0.071           0.074           0.024   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.028           0.010          -0.085          -0.131*  
                  (0.015)         (0.092)         (0.089)         (0.058)   
wp_right2_~x        0.037          -0.076           0.167          -0.100   
                  (0.023)         (0.123)         (0.213)         (0.096)   
c.neg#c.wp~x        0.012           0.009           0.291*          0.152   
                  (0.022)         (0.123)         (0.130)         (0.078)   
vid_order          -0.074***       -0.071*         -0.132***       -0.044*  
                  (0.005)         (0.030)         (0.030)         (0.019)   
female             -0.027          -0.091           0.181          -0.013   
                  (0.023)         (0.122)         (0.244)         (0.111)   
age                 0.001           0.013           0.035          -0.003   
                  (0.001)         (0.012)         (0.026)         (0.004)   
income              0.008           0.027          -0.153           0.043   
                  (0.049)         (0.282)         (0.451)         (0.204)   
university         -0.024          -0.011          -0.173          -0.078   
                  (0.024)         (0.132)         (0.328)         (0.110)   
_cons               0.228***        0.038          -0.462           0.353   
                  (0.052)         (0.335)         (0.811)         (0.237)   
----------------------------------------------------------------------------
r2_w                0.050           0.047           0.158           0.095   
r2_b                0.038           0.111           0.101           0.021   
r2_o                0.046           0.055           0.138           0.076   
N                4665.000         175.000         160.000         135.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.109          -0.004          -0.045   
                  (0.088)         (0.064)         (0.058)   
wp_right2_~x        0.145          -0.027           0.053   
                  (0.174)         (0.112)         (0.089)   
c.neg#c.wp~x       -0.073           0.069           0.127   
                  (0.124)         (0.098)         (0.081)   
vid_order          -0.109***       -0.111***       -0.043*  
                  (0.028)         (0.023)         (0.019)   
female              0.183           0.006           0.014   
                  (0.170)         (0.109)         (0.089)   
age                 0.005          -0.011           0.001   
                  (0.007)         (0.010)         (0.003)   
income              0.104           0.437           0.240   
                  (0.502)         (0.261)         (0.184)   
university          0.187          -0.136          -0.013   
                  (0.171)         (0.151)         (0.085)   
_cons              -0.232           0.628          -0.048   
                  (0.376)         (0.339)         (0.194)   
------------------------------------------------------------
r2_w                0.102           0.095           0.043   
r2_b                0.120           0.129           0.198   
r2_o                0.107           0.100           0.063   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.117           0.086           0.023   
                  (0.082)         (0.044)         (0.053)   
wp_right2_~x        0.012          -0.002          -0.116   
                  (0.133)         (0.059)         (0.084)   
c.neg#c.wp~x       -0.041          -0.091          -0.040   
                  (0.114)         (0.055)         (0.075)   
vid_order          -0.120***       -0.067***       -0.089***
                  (0.026)         (0.012)         (0.018)   
female             -0.106          -0.130*         -0.137   
                  (0.127)         (0.055)         (0.083)   
age                -0.004           0.001           0.002   
                  (0.006)         (0.003)         (0.006)   
income              0.038           0.148           0.146   
                  (0.302)         (0.107)         (0.170)   
university         -0.075          -0.037          -0.097   
                  (0.131)         (0.057)         (0.095)   
_cons               0.682*          0.205           0.275   
                  (0.317)         (0.124)         (0.183)   
------------------------------------------------------------
r2_w                0.106           0.114           0.098   
r2_b                0.058           0.190           0.194   
r2_o                0.095           0.131           0.118   
N                 255.000         300.000         250.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.020           0.094           0.043   
                  (0.078)         (0.099)         (0.040)   
wp_right2_~x        0.120          -0.146           0.042   
                  (0.137)         (0.153)         (0.075)   
c.neg#c.wp~x        0.000          -0.044          -0.032   
                  (0.112)         (0.147)         (0.059)   
vid_order          -0.132***       -0.051          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.125           0.066          -0.177*  
                  (0.129)         (0.153)         (0.082)   
age                -0.012           0.007           0.002   
                  (0.022)         (0.040)         (0.007)   
income             -0.417          -0.001           0.447*  
                  (0.294)         (0.371)         (0.226)   
university         -0.248          -0.098           0.168   
                  (0.187)         (0.292)         (0.123)   
_cons               1.122           0.096          -0.103   
                  (0.616)         (0.875)         (0.304)   
------------------------------------------------------------
r2_w                0.075           0.015           0.103   
r2_b                0.149           0.167           0.209   
r2_o                0.094           0.035           0.131   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2_dichox vid_order female age income u
&gt; niversity if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.038          -0.002           0.034          -0.015   
                  (0.095)         (0.061)         (0.070)         (0.027)   
wp_right2_~x        0.068           0.045           0.149           0.032   
                  (0.157)         (0.088)         (0.110)         (0.047)   
c.neg#c.wp~x        0.052           0.013           0.017           0.029   
                  (0.143)         (0.086)         (0.109)         (0.041)   
vid_order          -0.099**        -0.087***       -0.061*         -0.019*  
                  (0.034)         (0.021)         (0.026)         (0.009)   
female              0.087          -0.137           0.113          -0.011   
                  (0.152)         (0.091)         (0.103)         (0.048)   
age                -0.042          -0.004           0.005           0.003   
                  (0.047)         (0.002)         (0.005)         (0.002)   
income             -0.372           0.047          -0.082           0.191   
                  (0.291)         (0.155)         (0.264)         (0.144)   
university         -0.050           0.028          -0.035           0.014   
                  (0.232)         (0.096)         (0.162)         (0.047)   
_cons               1.444           0.469**        -0.009          -0.093   
                  (1.048)         (0.177)         (0.294)         (0.121)   
----------------------------------------------------------------------------
r2_w                0.053           0.102           0.041           0.017   
r2_b                0.194           0.300           0.259           0.113   
r2_o                0.077           0.134           0.078           0.041   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.053           0.086           0.039   
                  (0.060)         (0.064)         (0.035)   
wp_right2_~x        0.046           0.040           0.067   
                  (0.086)         (0.115)         (0.059)   
c.neg#c.wp~x        0.026          -0.034           0.028   
                  (0.081)         (0.087)         (0.050)   
vid_order          -0.025          -0.076***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.085          -0.093          -0.036   
                  (0.085)         (0.109)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.449*         -0.089          -0.020   
                  (0.222)         (0.220)         (0.121)   
university          0.067          -0.057           0.079   
                  (0.090)         (0.148)         (0.062)   
_cons               0.170           0.466*          0.016   
                  (0.195)         (0.223)         (0.133)   
------------------------------------------------------------
r2_w                0.018           0.078           0.021   
r2_b                0.215           0.070           0.030   
r2_o                0.059           0.075           0.023   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.    
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.006           0.024          -0.109          -0.049   
                  (0.023)         (0.126)         (0.137)         (0.066)   
left_right2        -0.028          -0.226          -0.629          -0.330*  
                  (0.045)         (0.251)         (0.576)         (0.167)   
c.neg#c.le~2        0.058          -0.021           0.516          -0.005   
                  (0.042)         (0.242)         (0.379)         (0.153)   
vid_order          -0.074***       -0.072*         -0.117***       -0.041*  
                  (0.005)         (0.030)         (0.031)         (0.019)   
female             -0.029          -0.080           0.148          -0.002   
                  (0.023)         (0.122)         (0.236)         (0.097)   
age                 0.001           0.011           0.018          -0.004   
                  (0.001)         (0.012)         (0.025)         (0.003)   
income              0.013           0.075          -0.107           0.080   
                  (0.049)         (0.290)         (0.439)         (0.196)   
university         -0.026          -0.008          -0.164          -0.076   
                  (0.024)         (0.130)         (0.317)         (0.105)   
_cons               0.257***        0.136           0.122           0.421   
                  (0.056)         (0.362)         (0.800)         (0.236)   
----------------------------------------------------------------------------
r2_w                0.050           0.047           0.135           0.058   
r2_b                0.034           0.127           0.105           0.149   
r2_o                0.046           0.058           0.124           0.081   
N                4660.000         175.000         160.000         135.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.031          -0.189          -0.021   
                  (0.119)         (0.182)         (0.097)   
left_right2        -0.244          -0.541*          0.203   
                  (0.400)         (0.256)         (0.202)   
c.neg#c.le~2        0.291           0.319           0.085   
                  (0.276)         (0.259)         (0.188)   
vid_order          -0.105***       -0.109***       -0.043*  
                  (0.029)         (0.022)         (0.019)   
female              0.221           0.033           0.004   
                  (0.181)         (0.098)         (0.083)   
age                 0.005          -0.011           0.001   
                  (0.007)         (0.010)         (0.003)   
income             -0.107           0.337           0.187   
                  (0.471)         (0.252)         (0.199)   
university          0.192          -0.090          -0.002   
                  (0.168)         (0.152)         (0.085)   
_cons              -0.040           0.978**        -0.095   
                  (0.379)         (0.373)         (0.201)   
------------------------------------------------------------
r2_w                0.103           0.099           0.036   
r2_b                0.126           0.213           0.166   
r2_o                0.109           0.116           0.052   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.065          -0.066           0.065   
                  (0.134)         (0.078)         (0.085)   
left_right2         0.107           0.023          -0.086   
                  (0.271)         (0.127)         (0.140)   
c.neg#c.le~2        0.058           0.142          -0.109   
                  (0.237)         (0.112)         (0.133)   
vid_order          -0.119***       -0.068***       -0.089***
                  (0.026)         (0.012)         (0.018)   
female             -0.113          -0.125*         -0.115   
                  (0.129)         (0.055)         (0.079)   
age                -0.004           0.001           0.001   
                  (0.006)         (0.003)         (0.005)   
income              0.053           0.144           0.153   
                  (0.305)         (0.109)         (0.167)   
university         -0.076          -0.029          -0.062   
                  (0.128)         (0.061)         (0.086)   
_cons               0.631           0.200           0.292   
                  (0.345)         (0.137)         (0.203)   
------------------------------------------------------------
r2_w                0.106           0.113           0.095   
r2_b                0.059           0.191           0.189   
r2_o                0.095           0.131           0.113   
N                 255.000         295.000         250.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.085           0.099           0.069   
                  (0.130)         (0.275)         (0.061)   
left_right2        -0.309           0.274           0.198   
                  (0.257)         (0.330)         (0.163)   
c.neg#c.le~2        0.125          -0.034          -0.101   
                  (0.218)         (0.342)         (0.131)   
vid_order          -0.132***       -0.050          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.134           0.123          -0.166*  
                  (0.131)         (0.155)         (0.081)   
age                -0.016           0.011           0.001   
                  (0.021)         (0.039)         (0.007)   
income             -0.420           0.020           0.423   
                  (0.297)         (0.371)         (0.224)   
university         -0.222          -0.120           0.185   
                  (0.192)         (0.292)         (0.122)   
_cons               1.437*         -0.285          -0.164   
                  (0.565)         (0.828)         (0.293)   
------------------------------------------------------------
r2_w                0.076           0.015           0.104   
r2_b                0.154           0.153           0.238   
r2_o                0.097           0.032           0.140   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.left_right2 vid_order female age income univer
&gt; sity if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.013          -0.154           0.169          -0.041   
                  (0.229)         (0.091)         (0.171)         (0.033)   
left_right2         0.227           0.112           0.343           0.029   
                  (0.465)         (0.235)         (0.377)         (0.065)   
c.neg#c.le~2        0.107           0.393*         -0.261           0.083   
                  (0.474)         (0.199)         (0.346)         (0.056)   
vid_order          -0.101**        -0.086***       -0.066*         -0.021*  
                  (0.034)         (0.021)         (0.026)         (0.010)   
female              0.056          -0.108           0.095          -0.007   
                  (0.142)         (0.103)         (0.110)         (0.047)   
age                -0.047          -0.003           0.005           0.002   
                  (0.045)         (0.002)         (0.006)         (0.002)   
income             -0.404           0.020          -0.008           0.184   
                  (0.283)         (0.151)         (0.268)         (0.141)   
university         -0.040           0.036          -0.073           0.004   
                  (0.229)         (0.092)         (0.160)         (0.045)   
_cons               1.497           0.440*         -0.061          -0.057   
                  (1.018)         (0.193)         (0.317)         (0.119)   
----------------------------------------------------------------------------
r2_w                0.052           0.127           0.048           0.023   
r2_b                0.197           0.307           0.191           0.119   
r2_o                0.076           0.157           0.072           0.046   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.150           0.111           0.044   
                  (0.086)         (0.109)         (0.049)   
left_right2         0.132           0.318           0.048   
                  (0.183)         (0.305)         (0.123)   
c.neg#c.le~2        0.242          -0.107           0.020   
                  (0.166)         (0.248)         (0.103)   
vid_order          -0.027          -0.076***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.086          -0.080          -0.035   
                  (0.083)         (0.109)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.494*         -0.120          -0.002   
                  (0.231)         (0.215)         (0.120)   
university          0.050          -0.055           0.078   
                  (0.086)         (0.147)         (0.062)   
_cons               0.178           0.344           0.014   
                  (0.192)         (0.251)         (0.141)   
------------------------------------------------------------
r2_w                0.032           0.078           0.020   
r2_b                0.236           0.087           0.024   
r2_o                0.075           0.080           0.021   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.020           0.021           0.063          -0.086   
                  (0.016)         (0.095)         (0.095)         (0.061)   
left_right~x       -0.021          -0.102          -0.089          -0.163*  
                  (0.023)         (0.121)         (0.212)         (0.082)   
c.neg#c.le~x        0.028          -0.008          -0.018           0.071   
                  (0.022)         (0.123)         (0.131)         (0.080)   
vid_order          -0.074***       -0.072*         -0.121***       -0.042*  
                  (0.005)         (0.030)         (0.031)         (0.019)   
female             -0.029          -0.076           0.143           0.034   
                  (0.023)         (0.123)         (0.246)         (0.092)   
age                 0.001           0.013           0.019          -0.003   
                  (0.001)         (0.012)         (0.027)         (0.003)   
income              0.014           0.015          -0.157           0.076   
                  (0.049)         (0.279)         (0.450)         (0.188)   
university         -0.026          -0.022          -0.147          -0.070   
                  (0.024)         (0.128)         (0.330)         (0.100)   
_cons               0.253***        0.084          -0.023           0.361   
                  (0.052)         (0.344)         (0.843)         (0.220)   
----------------------------------------------------------------------------
r2_w                0.050           0.048           0.128           0.066   
r2_b                0.035           0.120           0.060           0.117   
r2_o                0.046           0.057           0.103           0.079   
N                4660.000         175.000         160.000         135.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.020          -0.014           0.004   
                  (0.088)         (0.064)         (0.057)   
left_right~x       -0.152          -0.178          -0.007   
                  (0.187)         (0.096)         (0.089)   
c.neg#c.le~x        0.192           0.090           0.032   
                  (0.124)         (0.097)         (0.083)   
vid_order          -0.107***       -0.109***       -0.042*  
                  (0.028)         (0.022)         (0.020)   
female              0.234           0.052          -0.023   
                  (0.187)         (0.101)         (0.084)   
age                 0.006          -0.011           0.000   
                  (0.007)         (0.010)         (0.003)   
income             -0.165           0.434           0.279   
                  (0.487)         (0.250)         (0.193)   
university          0.175          -0.139          -0.010   
                  (0.170)         (0.149)         (0.087)   
_cons              -0.041           0.667*         -0.024   
                  (0.357)         (0.337)         (0.190)   
------------------------------------------------------------
r2_w                0.112           0.095           0.036   
r2_b                0.124           0.196           0.105   
r2_o                0.116           0.111           0.045   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.103          -0.005           0.024   
                  (0.080)         (0.037)         (0.052)   
left_right~x       -0.013           0.041          -0.094   
                  (0.130)         (0.058)         (0.077)   
c.neg#c.le~x       -0.015           0.064          -0.044   
                  (0.113)         (0.052)         (0.076)   
vid_order          -0.120***       -0.068***       -0.090***
                  (0.026)         (0.012)         (0.018)   
female             -0.105          -0.120*         -0.111   
                  (0.128)         (0.056)         (0.079)   
age                -0.004           0.001           0.001   
                  (0.006)         (0.003)         (0.005)   
income              0.032           0.129           0.147   
                  (0.305)         (0.109)         (0.163)   
university         -0.077          -0.026          -0.061   
                  (0.127)         (0.058)         (0.087)   
_cons               0.695*          0.201           0.283   
                  (0.326)         (0.123)         (0.178)   
------------------------------------------------------------
r2_w                0.105           0.112           0.095   
r2_b                0.057           0.202           0.202   
r2_o                0.095           0.133           0.116   
N                 255.000         295.000         250.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.043           0.130           0.040   
                  (0.077)         (0.097)         (0.043)   
left_right~x       -0.235           0.039           0.053   
                  (0.131)         (0.145)         (0.075)   
c.neg#c.le~x        0.054          -0.125          -0.024   
                  (0.111)         (0.148)         (0.059)   
vid_order          -0.132***       -0.049          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.127           0.099          -0.173*  
                  (0.129)         (0.153)         (0.081)   
age                -0.014           0.017           0.002   
                  (0.021)         (0.038)         (0.007)   
income             -0.395           0.014           0.440   
                  (0.293)         (0.372)         (0.225)   
university         -0.196          -0.134           0.188   
                  (0.189)         (0.292)         (0.128)   
_cons               1.293*         -0.164          -0.131   
                  (0.552)         (0.827)         (0.301)   
------------------------------------------------------------
r2_w                0.076           0.019           0.103   
r2_b                0.175           0.145           0.210   
r2_o                0.103           0.033           0.131   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.left_right2_dichox vid_order female age income
&gt;  university if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004          -0.096           0.180          -0.049   
                  (0.108)         (0.066)         (0.103)         (0.032)   
left_right~x        0.140          -0.022           0.207           0.047   
                  (0.146)         (0.098)         (0.125)         (0.046)   
c.neg#c.le~x        0.100           0.170*         -0.185           0.075   
                  (0.142)         (0.086)         (0.120)         (0.041)   
vid_order          -0.103**        -0.088***       -0.069**        -0.020*  
                  (0.034)         (0.021)         (0.026)         (0.009)   
female              0.021          -0.143           0.077          -0.010   
                  (0.147)         (0.098)         (0.109)         (0.047)   
age                -0.044          -0.003           0.004           0.002   
                  (0.044)         (0.002)         (0.005)         (0.002)   
income             -0.401           0.031           0.014           0.165   
                  (0.282)         (0.151)         (0.265)         (0.142)   
university         -0.063           0.036          -0.083           0.005   
                  (0.228)         (0.093)         (0.158)         (0.046)   
_cons               1.497           0.497**        -0.017          -0.071   
                  (0.940)         (0.188)         (0.290)         (0.119)   
----------------------------------------------------------------------------
r2_w                0.058           0.132           0.064           0.032   
r2_b                0.211           0.264           0.222           0.130   
r2_o                0.083           0.154           0.091           0.057   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.104           0.076           0.050   
                  (0.058)         (0.059)         (0.037)   
left_right~x        0.002           0.217*          0.007   
                  (0.085)         (0.106)         (0.060)   
c.neg#c.le~x        0.126          -0.016           0.004   
                  (0.081)         (0.087)         (0.051)   
vid_order          -0.027          -0.075***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.090          -0.054          -0.036   
                  (0.085)         (0.107)         (0.062)   
age                 0.003          -0.000           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.431          -0.169           0.003   
                  (0.229)         (0.210)         (0.120)   
university          0.053          -0.018           0.076   
                  (0.088)         (0.144)         (0.062)   
_cons               0.182           0.344           0.030   
                  (0.195)         (0.224)         (0.137)   
------------------------------------------------------------
r2_w                0.038           0.078           0.020   
r2_b                0.199           0.151           0.023   
r2_o                0.072           0.098           0.021   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.001          -0.155          -0.064   
                  (0.026)         (0.143)         (0.125)         (0.066)   
ideo_right2         0.015          -0.308          -0.427          -0.328   
                  (0.058)         (0.318)         (0.613)         (0.189)   
c.neg#c.id~2        0.075           0.032           0.773*          0.055   
                  (0.053)         (0.314)         (0.392)         (0.176)   
vid_order          -0.074***       -0.071*         -0.118***       -0.041*  
                  (0.005)         (0.030)         (0.030)         (0.019)   
female             -0.028          -0.079           0.158          -0.013   
                  (0.023)         (0.122)         (0.240)         (0.098)   
age                 0.001           0.011           0.022          -0.003   
                  (0.001)         (0.012)         (0.025)         (0.003)   
income              0.013           0.065          -0.181           0.064   
                  (0.049)         (0.287)         (0.434)         (0.196)   
university         -0.024          -0.008          -0.136          -0.066   
                  (0.025)         (0.130)         (0.318)         (0.104)   
_cons               0.235***        0.146          -0.033           0.377   
                  (0.058)         (0.363)         (0.790)         (0.232)   
----------------------------------------------------------------------------
r2_w                0.050           0.047           0.146           0.058   
r2_b                0.035           0.132           0.096           0.115   
r2_o                0.046           0.058           0.128           0.072   
N                4660.000         175.000         160.000         135.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014          -0.304          -0.062   
                  (0.135)         (0.243)         (0.095)   
ideo_right2         0.052          -0.828           0.176   
                  (0.525)         (0.427)         (0.241)   
c.neg#c.id~2        0.174           0.565           0.213   
                  (0.353)         (0.405)         (0.225)   
vid_order          -0.107***       -0.110***       -0.042*  
                  (0.029)         (0.022)         (0.019)   
female              0.178           0.059           0.003   
                  (0.180)         (0.102)         (0.085)   
age                 0.005          -0.010           0.001   
                  (0.007)         (0.010)         (0.003)   
income             -0.041           0.400           0.210   
                  (0.491)         (0.250)         (0.193)   
university          0.196          -0.072          -0.003   
                  (0.173)         (0.155)         (0.085)   
_cons              -0.151           1.021**        -0.075   
                  (0.422)         (0.389)         (0.203)   
------------------------------------------------------------
r2_w                0.099           0.101           0.037   
r2_b                0.111           0.190           0.171   
r2_o                0.103           0.115           0.054   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.063           0.017           0.135   
                  (0.139)         (0.147)         (0.120)   
ideo_right2         0.052           0.001          -0.280   
                  (0.344)         (0.252)         (0.233)   
c.neg#c.id~2        0.074           0.016          -0.224   
                  (0.291)         (0.224)         (0.195)   
vid_order          -0.119***       -0.067***       -0.088***
                  (0.026)         (0.012)         (0.018)   
female             -0.109          -0.133*         -0.103   
                  (0.129)         (0.055)         (0.080)   
age                -0.004           0.001           0.001   
                  (0.006)         (0.003)         (0.005)   
income              0.050           0.153           0.093   
                  (0.307)         (0.112)         (0.174)   
university         -0.081          -0.039          -0.089   
                  (0.128)         (0.059)         (0.090)   
_cons               0.666           0.210           0.412   
                  (0.343)         (0.178)         (0.234)   
------------------------------------------------------------
r2_w                0.106           0.103           0.098   
r2_b                0.055           0.203           0.211   
r2_o                0.095           0.126           0.121   
N                 255.000         295.000         250.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.200          -0.119           0.060   
                  (0.172)         (0.542)         (0.063)   
ideo_right2        -0.477          -0.019           0.186   
                  (0.512)         (0.972)         (0.210)   
c.neg#c.id~2        0.479           0.346          -0.098   
                  (0.431)         (0.950)         (0.168)   
vid_order          -0.134***       -0.052          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.138           0.090          -0.171*  
                  (0.133)         (0.155)         (0.081)   
age                -0.020           0.020           0.002   
                  (0.022)         (0.039)         (0.007)   
income             -0.467           0.030           0.432   
                  (0.294)         (0.379)         (0.226)   
university         -0.262          -0.104           0.179   
                  (0.188)         (0.294)         (0.123)   
_cons               1.600*         -0.214          -0.146   
                  (0.646)         (0.969)         (0.299)   
------------------------------------------------------------
r2_w                0.077           0.017           0.103   
r2_b                0.154           0.120           0.221   
r2_o                0.097           0.029           0.135   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.ideo_right2 vid_order female age income univer
&gt; sity if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.039          -0.123           0.175          -0.089   
                  (0.234)         (0.091)         (0.199)         (0.053)   
ideo_right2         0.264           0.197           0.547           0.049   
                  (0.575)         (0.262)         (0.401)         (0.109)   
c.neg#c.id~2        0.054           0.356          -0.246           0.165   
                  (0.553)         (0.223)         (0.370)         (0.092)   
vid_order          -0.100**        -0.086***       -0.061*         -0.021*  
                  (0.034)         (0.021)         (0.026)         (0.010)   
female              0.071          -0.090           0.083          -0.010   
                  (0.144)         (0.105)         (0.108)         (0.047)   
age                -0.043          -0.004           0.004           0.002   
                  (0.048)         (0.002)         (0.006)         (0.002)   
income             -0.388           0.053          -0.026           0.181   
                  (0.286)         (0.152)         (0.263)         (0.143)   
university         -0.053           0.027          -0.068           0.009   
                  (0.230)         (0.094)         (0.159)         (0.045)   
_cons               1.407           0.403*         -0.162          -0.068   
                  (1.119)         (0.198)         (0.330)         (0.119)   
----------------------------------------------------------------------------
r2_w                0.052           0.119           0.046           0.028   
r2_b                0.194           0.322           0.231           0.125   
r2_o                0.076           0.152           0.077           0.051   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.139           0.027           0.045   
                  (0.082)         (0.104)         (0.055)   
ideo_right2         0.135           0.186           0.090   
                  (0.196)         (0.337)         (0.147)   
c.neg#c.id~2        0.258           0.117           0.017   
                  (0.183)         (0.270)         (0.123)   
vid_order          -0.027          -0.076***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.092          -0.090          -0.034   
                  (0.083)         (0.109)         (0.062)   
age                 0.002          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.460*         -0.112          -0.006   
                  (0.221)         (0.219)         (0.120)   
university          0.049          -0.057           0.079   
                  (0.086)         (0.148)         (0.062)   
_cons               0.168           0.427           0.001   
                  (0.193)         (0.236)         (0.142)   
------------------------------------------------------------
r2_w                0.032           0.079           0.020   
r2_b                0.229           0.071           0.025   
r2_o                0.074           0.077           0.022   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A  
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store C
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store D
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store E
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store F
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.007           0.050          -0.037          -0.075   
                  (0.015)         (0.088)         (0.095)         (0.056)   
ideo_right~x       -0.020          -0.177           0.066          -0.135   
                  (0.023)         (0.124)         (0.210)         (0.083)   
c.neg#c.id~x        0.056**        -0.069           0.171           0.058   
                  (0.022)         (0.121)         (0.130)         (0.079)   
vid_order          -0.074***       -0.074*         -0.121***       -0.042*  
                  (0.005)         (0.029)         (0.030)         (0.019)   
female             -0.029          -0.055           0.169           0.013   
                  (0.023)         (0.123)         (0.244)         (0.096)   
age                 0.001           0.010           0.029          -0.002   
                  (0.001)         (0.012)         (0.026)         (0.003)   
income              0.012           0.000          -0.172           0.050   
                  (0.049)         (0.277)         (0.453)         (0.194)   
university         -0.026           0.027          -0.154          -0.041   
                  (0.024)         (0.132)         (0.329)         (0.103)   
_cons               0.253***        0.144          -0.320           0.285   
                  (0.052)         (0.341)         (0.796)         (0.218)   
----------------------------------------------------------------------------
r2_w                0.051           0.053           0.137           0.062   
r2_b                0.035           0.165           0.071           0.093   
r2_o                0.047           0.068           0.113           0.070   
N                4660.000         175.000         160.000         135.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.024           0.007          -0.057   
                  (0.088)         (0.063)         (0.057)   
ideo_right~x       -0.200          -0.269**         0.064   
                  (0.185)         (0.099)         (0.085)   
c.neg#c.id~x        0.194           0.058           0.153   
                  (0.124)         (0.097)         (0.081)   
vid_order          -0.106***       -0.111***       -0.041*  
                  (0.028)         (0.022)         (0.019)   
female              0.248           0.058           0.008   
                  (0.180)         (0.099)         (0.083)   
age                 0.007          -0.016           0.000   
                  (0.007)         (0.010)         (0.003)   
income             -0.216           0.502*          0.215   
                  (0.501)         (0.251)         (0.186)   
university          0.175          -0.103          -0.015   
                  (0.170)         (0.148)         (0.084)   
_cons              -0.044           0.791*         -0.023   
                  (0.355)         (0.340)         (0.185)   
------------------------------------------------------------
r2_w                0.114           0.093           0.051   
r2_b                0.132           0.279           0.213   
r2_o                0.119           0.122           0.071   
N                 180.000         280.000         175.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store H
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store I
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store J
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store K
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store L
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.122           0.028           0.032   
                  (0.082)         (0.038)         (0.055)   
ideo_right~x       -0.005          -0.008          -0.113   
                  (0.132)         (0.055)         (0.084)   
c.neg#c.id~x       -0.051          -0.001          -0.053   
                  (0.114)         (0.053)         (0.076)   
vid_order          -0.120***       -0.067***       -0.089***
                  (0.026)         (0.013)         (0.018)   
female             -0.106          -0.134*         -0.114   
                  (0.128)         (0.055)         (0.079)   
age                -0.004           0.001           0.003   
                  (0.006)         (0.003)         (0.006)   
income              0.028           0.155           0.097   
                  (0.307)         (0.106)         (0.171)   
university         -0.071          -0.040          -0.085   
                  (0.128)         (0.057)         (0.089)   
_cons               0.692*          0.212           0.258   
                  (0.324)         (0.122)         (0.176)   
------------------------------------------------------------
r2_w                0.106           0.103           0.096   
r2_b                0.059           0.204           0.204   
r2_o                0.095           0.126           0.118   
N                 255.000         295.000         250.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.093           0.023           0.044   
                  (0.079)         (0.107)         (0.042)   
ideo_right~x       -0.155          -0.048           0.051   
                  (0.128)         (0.150)         (0.075)   
c.neg#c.id~x        0.149           0.104          -0.033   
                  (0.111)         (0.148)         (0.059)   
vid_order          -0.133***       -0.054          -0.056***
                  (0.026)         (0.035)         (0.014)   
female             -0.140           0.080          -0.171*  
                  (0.130)         (0.156)         (0.081)   
age                -0.019           0.021           0.002   
                  (0.021)         (0.039)         (0.007)   
income             -0.464           0.017           0.443*  
                  (0.292)         (0.373)         (0.223)   
university         -0.261          -0.089           0.187   
                  (0.186)         (0.292)         (0.129)   
_cons               1.463**        -0.213          -0.131   
                  (0.559)         (0.823)         (0.301)   
------------------------------------------------------------
r2_w                0.078           0.019           0.104   
r2_b                0.165           0.122           0.207   
r2_o                0.101           0.031           0.132   
N                 355.000         160.000         185.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store N
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store O
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store P
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store S
.   quietly xtreg gslmc c.neg##c.ideo_right2_dichox vid_order female age income
&gt;  university if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.036          -0.108           0.043          -0.025   
                  (0.102)         (0.060)         (0.073)         (0.028)   
ideo_right~x       -0.014           0.087           0.193           0.025   
                  (0.146)         (0.101)         (0.110)         (0.047)   
c.neg#c.id~x        0.057           0.225**         0.005           0.047   
                  (0.142)         (0.083)         (0.106)         (0.040)   
vid_order          -0.099**        -0.083***       -0.061*         -0.021*  
                  (0.034)         (0.020)         (0.026)         (0.010)   
female              0.057          -0.071           0.098          -0.011   
                  (0.143)         (0.104)         (0.103)         (0.048)   
age                -0.052          -0.003           0.004           0.002   
                  (0.046)         (0.002)         (0.005)         (0.002)   
income             -0.402           0.049          -0.105           0.182   
                  (0.285)         (0.148)         (0.263)         (0.144)   
university         -0.042           0.060          -0.036           0.007   
                  (0.229)         (0.091)         (0.160)         (0.046)   
_cons               1.711           0.376*          0.007          -0.059   
                  (0.998)         (0.189)         (0.289)         (0.121)   
----------------------------------------------------------------------------
r2_w                0.053           0.146           0.041           0.021   
r2_b                0.185           0.339           0.300           0.109   
r2_o                0.076           0.178           0.085           0.043   
N                 180.000         160.000         160.000         240.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.104           0.047           0.039   
                  (0.058)         (0.062)         (0.035)   
ideo_right~x        0.002           0.149           0.044   
                  (0.085)         (0.105)         (0.059)   
c.neg#c.id~x        0.126           0.042           0.027   
                  (0.081)         (0.087)         (0.050)   
vid_order          -0.027          -0.077***       -0.042***
                  (0.020)         (0.020)         (0.012)   
female              0.090          -0.078          -0.036   
                  (0.085)         (0.106)         (0.062)   
age                 0.003          -0.001           0.002   
                  (0.003)         (0.004)         (0.003)   
income             -0.431          -0.122          -0.013   
                  (0.229)         (0.209)         (0.121)   
university          0.053          -0.034           0.080   
                  (0.088)         (0.144)         (0.062)   
_cons               0.182           0.420           0.019   
                  (0.195)         (0.220)         (0.134)   
------------------------------------------------------------
r2_w                0.038           0.080           0.021   
r2_b                0.199           0.110           0.025   
r2_o                0.072           0.088           0.022   
N                 155.000         240.000         920.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.   
. * Table A6 Row 5
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(56,936 real changes made, 39,228 to missing)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.007   
                  (0.003)         (0.017)         (0.013)   
wp_right2           0.050          -0.105           0.009   
                  (0.037)         (0.214)         (0.220)   
c.neg#c.wp~2       -0.012           0.011           0.015   
                  (0.007)         (0.042)         (0.040)   
pho_order           0.002***        0.005*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.023           0.070   
                  (0.007)         (0.037)         (0.061)   
age                -0.000          -0.002           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.018          -0.087          -0.145   
                  (0.015)         (0.079)         (0.118)   
university          0.006           0.015           0.121   
                  (0.007)         (0.037)         (0.063)   
_cons              -0.070**         0.008          -0.178   
                  (0.023)         (0.131)         (0.142)   
------------------------------------------------------------
r2_w                0.003           0.013           0.014   
r2_b                0.015           0.178           0.232   
r2_o                0.003           0.018           0.032   
N               15263.000         623.000         513.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003          -0.009           0.007   
                  (0.016)         (0.027)         (0.009)   
wp_right2          -0.288          -0.071          -0.026   
                  (0.230)         (0.274)         (0.145)   
c.neg#c.wp~2        0.037           0.030          -0.004   
                  (0.044)         (0.052)         (0.026)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.031           0.039          -0.067*  
                  (0.040)         (0.036)         (0.028)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income             -0.005           0.013           0.036   
                  (0.115)         (0.095)         (0.060)   
university         -0.051           0.012          -0.013   
                  (0.041)         (0.053)         (0.028)   
_cons               0.073          -0.070          -0.060   
                  (0.125)         (0.174)         (0.075)   
------------------------------------------------------------
r2_w                0.003           0.002           0.012   
r2_b                0.155           0.056           0.192   
r2_o                0.008           0.004           0.027   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.030*          0.014           0.005           0.012   
                  (0.015)         (0.015)         (0.017)         (0.013)   
wp_right2           0.212           0.020           0.061           0.322   
                  (0.197)         (0.124)         (0.136)         (0.205)   
c.neg#c.wp~2       -0.029          -0.015          -0.015          -0.041   
                  (0.038)         (0.023)         (0.026)         (0.037)   
pho_order           0.005*          0.003*          0.001           0.001   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.018           0.020           0.026           0.004   
                  (0.030)         (0.022)         (0.025)         (0.039)   
age                 0.000          -0.000          -0.001           0.002   
                  (0.002)         (0.001)         (0.002)         (0.005)   
income             -0.046          -0.025          -0.029          -0.029   
                  (0.074)         (0.043)         (0.055)         (0.078)   
university          0.072*         -0.022           0.020           0.007   
                  (0.030)         (0.023)         (0.029)         (0.055)   
_cons              -0.283**        -0.045          -0.014          -0.143   
                  (0.106)         (0.090)         (0.104)         (0.173)   
----------------------------------------------------------------------------
r2_w                0.016           0.006           0.002           0.003   
r2_b                0.267           0.073           0.064           0.115   
r2_o                0.024           0.011           0.004           0.008   
N                 969.000        1140.000         911.000         456.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.037           0.008           0.027   
                  (0.019)         (0.010)         (0.026)   
wp_right2          -0.385           0.020           0.061   
                  (0.247)         (0.178)         (0.359)   
c.neg#c.wp~2        0.072          -0.012          -0.015   
                  (0.048)         (0.035)         (0.068)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.032          -0.032           0.019   
                  (0.044)         (0.026)         (0.054)   
age                 0.005          -0.002           0.014   
                  (0.011)         (0.002)         (0.018)   
income             -0.145           0.120           0.058   
                  (0.106)         (0.072)         (0.105)   
university          0.133          -0.004          -0.105   
                  (0.119)         (0.039)         (0.085)   
_cons              -0.064          -0.048          -0.282   
                  (0.266)         (0.107)         (0.423)   
------------------------------------------------------------
r2_w                0.017           0.011           0.007   
r2_b                0.212           0.124           0.095   
r2_o                0.030           0.017           0.010   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.046***        0.057**        -0.009   
                  (0.013)         (0.019)         (0.011)   
wp_right2           0.201           0.402*         -0.093   
                  (0.191)         (0.164)         (0.088)   
c.neg#c.wp~2       -0.077*         -0.072*          0.019   
                  (0.035)         (0.032)         (0.017)   
pho_order           0.001          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.003          -0.014           0.016   
                  (0.043)         (0.032)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.001          -0.061          -0.037   
                  (0.068)         (0.080)         (0.043)   
university         -0.013          -0.036           0.001   
                  (0.041)         (0.048)         (0.014)   
_cons              -0.133          -0.170           0.056   
                  (0.102)         (0.127)         (0.064)   
------------------------------------------------------------
r2_w                0.025           0.018           0.004   
r2_b                0.163           0.136           0.108   
r2_o                0.033           0.022           0.006   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009           0.009           0.016   
                  (0.011)         (0.012)         (0.011)   
wp_right2          -0.104           0.046           0.100   
                  (0.152)         (0.178)         (0.142)   
c.neg#c.wp~2        0.015          -0.018          -0.019   
                  (0.029)         (0.034)         (0.028)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.059           0.053           0.005   
                  (0.032)         (0.030)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income             -0.012          -0.078           0.045   
                  (0.082)         (0.061)         (0.045)   
university          0.022          -0.053           0.021   
                  (0.033)         (0.041)         (0.023)   
_cons              -0.154           0.010          -0.090   
                  (0.090)         (0.087)         (0.072)   
------------------------------------------------------------
r2_w                0.009           0.002           0.002   
r2_b                0.193           0.152           0.033   
r2_o                0.020           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011***        0.009           0.011   
                  (0.002)         (0.009)         (0.009)   
wp_right2_~2        0.039*         -0.019           0.075   
                  (0.017)         (0.084)         (0.120)   
c.neg#c.wp~2       -0.008*          0.002          -0.003   
                  (0.003)         (0.016)         (0.022)   
pho_order           0.002***        0.005*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.025           0.066   
                  (0.007)         (0.037)         (0.058)   
age                -0.000          -0.002          -0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.017          -0.089          -0.125   
                  (0.015)         (0.080)         (0.118)   
university          0.007           0.012           0.115   
                  (0.007)         (0.036)         (0.062)   
_cons              -0.065***       -0.021          -0.188   
                  (0.018)         (0.113)         (0.131)   
------------------------------------------------------------
r2_w                0.003           0.013           0.014   
r2_b                0.015           0.165           0.251   
r2_o                0.004           0.017           0.034   
N               15263.000         623.000         513.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010          -0.000           0.007   
                  (0.010)         (0.013)         (0.005)   
wp_right2_~2       -0.025           0.003           0.026   
                  (0.112)         (0.079)         (0.061)   
c.neg#c.wp~2       -0.004           0.009          -0.006   
                  (0.022)         (0.015)         (0.011)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.031           0.037          -0.062*  
                  (0.040)         (0.035)         (0.027)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income              0.019           0.000           0.031   
                  (0.111)         (0.095)         (0.061)   
university         -0.050           0.012          -0.012   
                  (0.041)         (0.052)         (0.028)   
_cons              -0.030          -0.102          -0.073   
                  (0.097)         (0.131)         (0.063)   
------------------------------------------------------------
r2_w                0.002           0.002           0.012   
r2_b                0.137           0.085           0.185   
r2_o                0.006           0.006           0.027   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.024**         0.005           0.000           0.001   
                  (0.008)         (0.013)         (0.011)         (0.008)   
wp_right2_~2        0.078          -0.004           0.022           0.093   
                  (0.089)         (0.072)         (0.065)         (0.098)   
c.neg#c.wp~2       -0.016          -0.000          -0.007          -0.006   
                  (0.017)         (0.013)         (0.013)         (0.019)   
pho_order           0.005*          0.003*          0.001           0.001   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.019           0.019           0.025           0.016   
                  (0.030)         (0.022)         (0.025)         (0.041)   
age                 0.001          -0.000          -0.001           0.002   
                  (0.002)         (0.001)         (0.002)         (0.005)   
income             -0.056          -0.028          -0.029          -0.035   
                  (0.077)         (0.043)         (0.054)         (0.076)   
university          0.075*         -0.025           0.019           0.002   
                  (0.030)         (0.023)         (0.029)         (0.055)   
_cons              -0.233**        -0.023           0.006          -0.048   
                  (0.084)         (0.081)         (0.077)         (0.136)   
----------------------------------------------------------------------------
r2_w                0.016           0.006           0.002           0.001   
r2_b                0.244           0.063           0.066           0.136   
r2_o                0.023           0.010           0.004           0.007   
N                 969.000        1140.000         911.000         456.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.010           0.005           0.018   
                  (0.010)         (0.005)         (0.013)   
wp_right2_~2       -0.013          -0.053          -0.028   
                  (0.105)         (0.115)         (0.147)   
c.neg#c.wp~2       -0.001           0.000           0.016   
                  (0.020)         (0.022)         (0.028)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.034          -0.035           0.025   
                  (0.044)         (0.026)         (0.052)   
age                 0.005          -0.002           0.019   
                  (0.012)         (0.002)         (0.017)   
income             -0.140           0.125           0.068   
                  (0.105)         (0.072)         (0.103)   
university          0.143          -0.014          -0.124   
                  (0.121)         (0.040)         (0.087)   
_cons              -0.209          -0.030          -0.342   
                  (0.245)         (0.096)         (0.366)   
------------------------------------------------------------
r2_w                0.013           0.011           0.008   
r2_b                0.209           0.146           0.116   
r2_o                0.026           0.018           0.011   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dicho2 pho_order female age in
&gt; come university if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.026**         0.041**        -0.003   
                  (0.008)         (0.013)         (0.006)   
wp_right2_~2        0.051           0.196*         -0.013   
                  (0.089)         (0.081)         (0.037)   
c.neg#c.wp~2       -0.019          -0.035*          0.006   
                  (0.016)         (0.016)         (0.007)   
pho_order           0.001          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.020          -0.015           0.015   
                  (0.043)         (0.032)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.022          -0.071          -0.042   
                  (0.068)         (0.081)         (0.042)   
university         -0.018          -0.030           0.006   
                  (0.045)         (0.049)         (0.014)   
_cons              -0.092          -0.086           0.010   
                  (0.085)         (0.107)         (0.048)   
------------------------------------------------------------
r2_w                0.019           0.018           0.003   
r2_b                0.112           0.135           0.140   
r2_o                0.024           0.022           0.006   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012           0.007           0.015** 
                  (0.008)         (0.007)         (0.005)   
wp_right2_~2       -0.033           0.084           0.102   
                  (0.079)         (0.088)         (0.059)   
c.neg#c.wp~2        0.010          -0.020          -0.023   
                  (0.015)         (0.017)         (0.012)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.065*          0.052           0.004   
                  (0.033)         (0.031)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income             -0.007          -0.082           0.047   
                  (0.084)         (0.060)         (0.045)   
university          0.020          -0.053           0.020   
                  (0.033)         (0.042)         (0.022)   
_cons              -0.173*          0.014          -0.078   
                  (0.082)         (0.073)         (0.055)   
------------------------------------------------------------
r2_w                0.009           0.003           0.003   
r2_b                0.189           0.148           0.033   
r2_o                0.019           0.011           0.004   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.   
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.004          -0.000   
                  (0.002)         (0.011)         (0.013)   
wp_right2_~x        0.001          -0.080          -0.076   
                  (0.016)         (0.078)         (0.097)   
c.neg#c.wp~x       -0.002           0.010           0.019   
                  (0.003)         (0.015)         (0.017)   
pho_order           0.002***        0.005*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.011          -0.026           0.065   
                  (0.007)         (0.036)         (0.065)   
age                -0.000          -0.003           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.017          -0.078          -0.144   
                  (0.015)         (0.080)         (0.119)   
university          0.006           0.019           0.121   
                  (0.007)         (0.037)         (0.064)   
_cons              -0.051**         0.013          -0.134   
                  (0.019)         (0.116)         (0.142)   
------------------------------------------------------------
r2_w                0.003           0.013           0.016   
r2_b                0.016           0.214           0.219   
r2_o                0.003           0.019           0.033   
N               15263.000         623.000         513.000   
N_g               804.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.007           0.004           0.008   
                  (0.012)         (0.009)         (0.006)   
wp_right2_~x       -0.051          -0.009           0.003   
                  (0.089)         (0.077)         (0.050)   
c.neg#c.wp~x        0.003           0.005          -0.004   
                  (0.017)         (0.015)         (0.009)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.027           0.040          -0.068*  
                  (0.040)         (0.038)         (0.029)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income             -0.004           0.013           0.037   
                  (0.117)         (0.096)         (0.060)   
university         -0.040           0.015          -0.013   
                  (0.040)         (0.052)         (0.028)   
_cons              -0.003          -0.113          -0.066   
                  (0.106)         (0.126)         (0.068)   
------------------------------------------------------------
r2_w                0.002           0.001           0.012   
r2_b                0.139           0.053           0.193   
r2_o                0.007           0.004           0.027   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.026**         0.012          -0.007           0.020   
                  (0.010)         (0.007)         (0.008)         (0.012)   
wp_right2_~x        0.059           0.036          -0.038           0.218** 
                  (0.071)         (0.045)         (0.056)         (0.082)   
c.neg#c.wp~x       -0.011          -0.010           0.005          -0.034*  
                  (0.014)         (0.008)         (0.011)         (0.015)   
pho_order           0.005*          0.003*          0.001           0.000   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.020           0.017           0.025          -0.012   
                  (0.030)         (0.022)         (0.025)         (0.040)   
age                 0.001          -0.000          -0.001           0.002   
                  (0.002)         (0.001)         (0.002)         (0.004)   
income             -0.059          -0.028          -0.029          -0.034   
                  (0.072)         (0.043)         (0.054)         (0.075)   
university          0.072*         -0.025           0.017           0.009   
                  (0.031)         (0.023)         (0.029)         (0.054)   
_cons              -0.244**        -0.053           0.041          -0.151   
                  (0.089)         (0.057)         (0.067)         (0.144)   
----------------------------------------------------------------------------
r2_w                0.016           0.007           0.002           0.012   
r2_b                0.247           0.067           0.072           0.149   
r2_o                0.023           0.012           0.004           0.018   
N                 969.000        1140.000         911.000         456.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.022           0.007           0.018   
                  (0.012)         (0.007)         (0.015)   
wp_right2_~x       -0.133           0.007          -0.056   
                  (0.092)         (0.052)         (0.118)   
c.neg#c.wp~x        0.023          -0.004           0.008   
                  (0.018)         (0.010)         (0.023)   
pho_order           0.007*          0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.040          -0.032           0.013   
                  (0.045)         (0.026)         (0.055)   
age                 0.005          -0.002           0.013   
                  (0.011)         (0.002)         (0.017)   
income             -0.140           0.118           0.051   
                  (0.103)         (0.072)         (0.105)   
university          0.123          -0.004          -0.102   
                  (0.120)         (0.039)         (0.084)   
_cons              -0.116          -0.043          -0.197   
                  (0.258)         (0.102)         (0.384)   
------------------------------------------------------------
r2_w                0.016           0.011           0.007   
r2_b                0.213           0.125           0.099   
r2_o                0.029           0.017           0.010   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2_dichox pho_order female age in
&gt; come university if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.027**         0.032***       -0.003   
                  (0.010)         (0.009)         (0.004)   
wp_right2_~x       -0.014           0.148*         -0.064*  
                  (0.074)         (0.072)         (0.031)   
c.neg#c.wp~x       -0.010          -0.036*          0.011   
                  (0.014)         (0.014)         (0.006)   
pho_order           0.002          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.016          -0.007           0.017   
                  (0.038)         (0.031)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.013          -0.053          -0.031   
                  (0.064)         (0.080)         (0.042)   
university         -0.016          -0.043           0.000   
                  (0.040)         (0.049)         (0.014)   
_cons              -0.078          -0.024           0.027   
                  (0.088)         (0.097)         (0.041)   
------------------------------------------------------------
r2_w                0.018           0.020           0.006   
r2_b                0.185           0.111           0.152   
r2_o                0.027           0.024           0.009   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014           0.004           0.012   
                  (0.010)         (0.009)         (0.006)   
wp_right2_~x       -0.030          -0.011           0.030   
                  (0.070)         (0.067)         (0.050)   
c.neg#c.wp~x       -0.000          -0.000          -0.005   
                  (0.013)         (0.013)         (0.010)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.060           0.053           0.005   
                  (0.031)         (0.030)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income              0.001          -0.078           0.044   
                  (0.083)         (0.061)         (0.045)   
university          0.014          -0.055           0.021   
                  (0.033)         (0.041)         (0.022)   
_cons              -0.177*          0.030          -0.066   
                  (0.085)         (0.079)         (0.057)   
------------------------------------------------------------
r2_w                0.008           0.001           0.002   
r2_b                0.214           0.151           0.034   
r2_o                0.020           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.    
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012***        0.018           0.012   
                  (0.003)         (0.015)         (0.015)   
left_right2         0.038           0.092          -0.003   
                  (0.031)         (0.151)         (0.185)   
c.neg#c.le~2       -0.008          -0.017          -0.004   
                  (0.006)         (0.029)         (0.034)   
pho_order           0.002***        0.006*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.028           0.058   
                  (0.007)         (0.036)         (0.059)   
age                -0.000          -0.002           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.018          -0.098          -0.142   
                  (0.015)         (0.082)         (0.119)   
university          0.007           0.011           0.119   
                  (0.007)         (0.037)         (0.064)   
_cons              -0.068**        -0.063          -0.173   
                  (0.023)         (0.131)         (0.153)   
------------------------------------------------------------
r2_w                0.003           0.013           0.014   
r2_b                0.015           0.164           0.218   
r2_o                0.003           0.018           0.031   
N               15244.000         623.000         513.000   
N_g               803.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.003          -0.010           0.010   
                  (0.016)         (0.032)         (0.010)   
left_right2        -0.095           0.087           0.040   
                  (0.198)         (0.230)         (0.114)   
c.neg#c.le~2        0.014           0.023          -0.009   
                  (0.038)         (0.045)         (0.020)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.030           0.040          -0.061*  
                  (0.043)         (0.034)         (0.027)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income              0.027           0.007           0.030   
                  (0.112)         (0.094)         (0.065)   
university         -0.041          -0.004          -0.012   
                  (0.040)         (0.053)         (0.028)   
_cons              -0.003          -0.167          -0.086   
                  (0.119)         (0.200)         (0.079)   
------------------------------------------------------------
r2_w                0.002           0.002           0.012   
r2_b                0.104           0.121           0.184   
r2_o                0.006           0.007           0.027   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.023           0.008          -0.002          -0.022   
                  (0.016)         (0.012)         (0.013)         (0.017)   
left_right2         0.106          -0.026           0.020          -0.180   
                  (0.148)         (0.094)         (0.102)         (0.140)   
c.neg#c.le~2       -0.006          -0.004          -0.005           0.040   
                  (0.029)         (0.017)         (0.020)         (0.027)   
pho_order           0.004*          0.003*          0.001           0.000   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.015           0.016           0.027           0.002   
                  (0.031)         (0.023)         (0.025)         (0.042)   
age                 0.001          -0.000          -0.001          -0.001   
                  (0.001)         (0.001)         (0.002)         (0.004)   
income             -0.051          -0.019          -0.028          -0.060   
                  (0.073)         (0.044)         (0.055)         (0.078)   
university          0.078*         -0.034           0.021          -0.001   
                  (0.030)         (0.025)         (0.027)         (0.057)   
_cons              -0.268*         -0.016           0.014           0.159   
                  (0.111)         (0.078)         (0.087)         (0.141)   
----------------------------------------------------------------------------
r2_w                0.015           0.006           0.002           0.006   
r2_b                0.291           0.077           0.063           0.048   
r2_o                0.024           0.011           0.004           0.007   
N                 969.000        1121.000         911.000         456.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.033           0.013           0.001   
                  (0.032)         (0.011)         (0.036)   
left_right2         0.247           0.067          -0.056   
                  (0.206)         (0.117)         (0.380)   
c.neg#c.le~2       -0.057          -0.018           0.044   
                  (0.040)         (0.023)         (0.074)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.035          -0.032           0.018   
                  (0.045)         (0.026)         (0.052)   
age                 0.006          -0.002           0.018   
                  (0.011)         (0.002)         (0.016)   
income             -0.133           0.118           0.060   
                  (0.104)         (0.073)         (0.102)   
university          0.140          -0.004          -0.103   
                  (0.120)         (0.040)         (0.083)   
_cons              -0.427          -0.074          -0.311   
                  (0.276)         (0.106)         (0.406)   
------------------------------------------------------------
r2_w                0.017           0.012           0.008   
r2_b                0.207           0.121           0.130   
r2_o                0.029           0.017           0.012   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.left_right2 pho_order female age income 
&gt; university if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.029           0.030          -0.005   
                  (0.015)         (0.020)         (0.005)   
left_right2         0.085           0.164          -0.050   
                  (0.186)         (0.219)         (0.043)   
c.neg#c.le~2       -0.017          -0.031           0.014   
                  (0.033)         (0.042)         (0.008)   
pho_order           0.002          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.037          -0.011           0.015   
                  (0.046)         (0.033)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.032          -0.054          -0.047   
                  (0.067)         (0.082)         (0.043)   
university         -0.032          -0.037           0.002   
                  (0.041)         (0.049)         (0.014)   
_cons              -0.118          -0.029           0.032   
                  (0.110)         (0.133)         (0.043)   
------------------------------------------------------------
r2_w                0.017           0.010           0.005   
r2_b                0.093           0.101           0.130   
r2_o                0.022           0.014           0.008   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.007           0.016           0.012   
                  (0.014)         (0.016)         (0.009)   
left_right2        -0.147           0.111           0.009   
                  (0.144)         (0.184)         (0.104)   
c.neg#c.le~2        0.015          -0.029          -0.006   
                  (0.028)         (0.036)         (0.020)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.062*          0.052           0.004   
                  (0.031)         (0.031)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income              0.024          -0.081           0.049   
                  (0.087)         (0.061)         (0.045)   
university          0.025          -0.054           0.019   
                  (0.033)         (0.042)         (0.023)   
_cons              -0.150          -0.014          -0.060   
                  (0.096)         (0.104)         (0.066)   
------------------------------------------------------------
r2_w                0.009           0.002           0.002   
r2_b                0.224           0.149           0.034   
r2_o                0.021           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.    
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.006**         0.018           0.008   
                  (0.002)         (0.012)         (0.013)   
left_right~x       -0.019           0.063          -0.063   
                  (0.016)         (0.078)         (0.095)   
c.neg#c.le~x        0.004          -0.014           0.004   
                  (0.003)         (0.015)         (0.017)   
pho_order           0.002***        0.006*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.027           0.062   
                  (0.007)         (0.036)         (0.058)   
age                -0.000          -0.003          -0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.017          -0.094          -0.133   
                  (0.015)         (0.079)         (0.118)   
university          0.006           0.012           0.114   
                  (0.007)         (0.036)         (0.063)   
_cons              -0.040*         -0.057          -0.135   
                  (0.019)         (0.118)         (0.143)   
------------------------------------------------------------
r2_w                0.003           0.014           0.014   
r2_b                0.015           0.162           0.245   
r2_o                0.003           0.018           0.033   
N               15244.000         623.000         513.000   
N_g               803.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.006           0.001           0.010   
                  (0.012)         (0.010)         (0.006)   
left_right~x       -0.030          -0.023           0.050   
                  (0.090)         (0.074)         (0.050)   
c.neg#c.le~x        0.004           0.011          -0.010   
                  (0.017)         (0.014)         (0.009)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.029           0.038          -0.059*  
                  (0.044)         (0.035)         (0.027)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income              0.026           0.017           0.026   
                  (0.114)         (0.094)         (0.063)   
university         -0.041           0.016          -0.010   
                  (0.040)         (0.051)         (0.029)   
_cons              -0.024          -0.101          -0.090   
                  (0.103)         (0.126)         (0.066)   
------------------------------------------------------------
r2_w                0.002           0.002           0.013   
r2_b                0.102           0.065           0.186   
r2_o                0.005           0.005           0.028   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.024*          0.004          -0.002          -0.009   
                  (0.010)         (0.006)         (0.008)         (0.010)   
left_right~x        0.063          -0.053           0.007          -0.097   
                  (0.070)         (0.044)         (0.055)         (0.080)   
c.neg#c.le~x       -0.009           0.002          -0.005           0.021   
                  (0.014)         (0.008)         (0.011)         (0.015)   
pho_order           0.005*          0.003*          0.001           0.001   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.017           0.009           0.028           0.001   
                  (0.031)         (0.022)         (0.025)         (0.041)   
age                 0.001          -0.000          -0.001          -0.001   
                  (0.001)         (0.001)         (0.002)         (0.004)   
income             -0.051          -0.010          -0.031          -0.059   
                  (0.073)         (0.043)         (0.054)         (0.078)   
university          0.076*         -0.037           0.021           0.000   
                  (0.030)         (0.023)         (0.027)         (0.059)   
_cons              -0.250**        -0.007           0.021           0.098   
                  (0.090)         (0.055)         (0.067)         (0.124)   
----------------------------------------------------------------------------
r2_w                0.015           0.006           0.002           0.005   
r2_b                0.263           0.118           0.079           0.047   
r2_o                0.023           0.014           0.004           0.007   
N                 969.000        1121.000         911.000         456.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.008           0.005   
                  (0.012)         (0.007)         (0.017)   
left_right~x        0.087           0.032          -0.090   
                  (0.092)         (0.052)         (0.117)   
c.neg#c.le~x       -0.020          -0.006           0.029   
                  (0.018)         (0.010)         (0.023)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.033          -0.031           0.008   
                  (0.044)         (0.026)         (0.053)   
age                 0.006          -0.002           0.016   
                  (0.011)         (0.002)         (0.016)   
income             -0.134           0.115           0.062   
                  (0.104)         (0.073)         (0.102)   
university          0.138           0.000          -0.110   
                  (0.120)         (0.041)         (0.083)   
_cons              -0.267          -0.068          -0.245   
                  (0.240)         (0.103)         (0.351)   
------------------------------------------------------------
r2_w                0.015           0.011           0.010   
r2_b                0.207           0.119           0.127   
r2_o                0.028           0.017           0.013   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.left_right2_dichox pho_order female age 
&gt; income university if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.018           0.024          -0.008   
                  (0.011)         (0.013)         (0.005)   
left_right~x       -0.042           0.042          -0.062*  
                  (0.079)         (0.081)         (0.031)   
c.neg#c.le~x        0.006          -0.011           0.016*  
                  (0.014)         (0.016)         (0.006)   
pho_order           0.002          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.029          -0.007           0.016   
                  (0.043)         (0.033)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.034          -0.060          -0.047   
                  (0.067)         (0.082)         (0.043)   
university         -0.034          -0.038           0.002   
                  (0.041)         (0.049)         (0.014)   
_cons              -0.057           0.011           0.044   
                  (0.097)         (0.107)         (0.042)   
------------------------------------------------------------
r2_w                0.017           0.010           0.010   
r2_b                0.097           0.101           0.134   
r2_o                0.022           0.013           0.012   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.008           0.007           0.006   
                  (0.010)         (0.009)         (0.007)   
left_right~x       -0.112           0.005          -0.043   
                  (0.069)         (0.066)         (0.050)   
c.neg#c.le~x        0.012          -0.006           0.007   
                  (0.013)         (0.013)         (0.010)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.059           0.049           0.002   
                  (0.031)         (0.030)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income              0.030          -0.074           0.049   
                  (0.085)         (0.060)         (0.045)   
university          0.018          -0.058           0.018   
                  (0.033)         (0.041)         (0.023)   
_cons              -0.157           0.032          -0.034   
                  (0.084)         (0.078)         (0.059)   
------------------------------------------------------------
r2_w                0.010           0.002           0.002   
r2_b                0.279           0.161           0.036   
r2_o                0.026           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.     
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***        0.014           0.009   
                  (0.004)         (0.017)         (0.015)   
ideo_right2         0.061           0.033           0.002   
                  (0.040)         (0.198)         (0.211)   
c.neg#c.id~2       -0.014          -0.010           0.004   
                  (0.008)         (0.038)         (0.039)   
pho_order           0.002***        0.006*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.026           0.061   
                  (0.007)         (0.036)         (0.060)   
age                -0.000          -0.003           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.018          -0.091          -0.145   
                  (0.015)         (0.081)         (0.119)   
university          0.007           0.013           0.121   
                  (0.007)         (0.037)         (0.064)   
_cons              -0.077**        -0.035          -0.180   
                  (0.025)         (0.135)         (0.149)   
------------------------------------------------------------
r2_w                0.003           0.013           0.014   
r2_b                0.014           0.163           0.218   
r2_o                0.003           0.017           0.031   
N               15244.000         623.000         513.000   
N_g               803.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002          -0.020           0.009   
                  (0.018)         (0.038)         (0.010)   
ideo_right2        -0.242           0.073           0.017   
                  (0.247)         (0.330)         (0.137)   
c.neg#c.id~2        0.032           0.044          -0.008   
                  (0.047)         (0.063)         (0.024)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.035           0.027          -0.064*  
                  (0.042)         (0.035)         (0.028)   
age                -0.001           0.001          -0.000   
                  (0.002)         (0.003)         (0.001)   
income              0.009          -0.004           0.036   
                  (0.114)         (0.094)         (0.063)   
university         -0.045          -0.010          -0.012   
                  (0.040)         (0.054)         (0.028)   
_cons               0.053          -0.124          -0.075   
                  (0.130)         (0.223)         (0.079)   
------------------------------------------------------------
r2_w                0.003           0.002           0.012   
r2_b                0.129           0.113           0.186   
r2_o                0.007           0.007           0.027   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.028           0.022           0.006          -0.011   
                  (0.017)         (0.022)         (0.019)         (0.020)   
ideo_right2         0.173          -0.035           0.069          -0.055   
                  (0.182)         (0.185)         (0.163)         (0.229)   
c.neg#c.id~2       -0.017          -0.026          -0.017           0.026   
                  (0.035)         (0.034)         (0.031)         (0.044)   
pho_order           0.004*          0.003*          0.001           0.001   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.016           0.016           0.027           0.008   
                  (0.031)         (0.022)         (0.025)         (0.042)   
age                 0.001           0.000          -0.001          -0.000   
                  (0.002)         (0.001)         (0.002)         (0.004)   
income             -0.047          -0.009          -0.029          -0.055   
                  (0.073)         (0.044)         (0.056)         (0.077)   
university          0.075*         -0.037           0.021          -0.002   
                  (0.030)         (0.024)         (0.028)         (0.057)   
_cons              -0.284*         -0.024          -0.015           0.058   
                  (0.113)         (0.125)         (0.117)         (0.168)   
----------------------------------------------------------------------------
r2_w                0.015           0.006           0.002           0.001   
r2_b                0.285           0.106           0.064           0.065   
r2_o                0.024           0.014           0.004           0.004   
N                 969.000        1121.000         911.000         456.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.007           0.012           0.015   
                  (0.064)         (0.011)         (0.036)   
ideo_right2        -0.095           0.063           0.024   
                  (0.585)         (0.151)         (0.441)   
c.neg#c.id~2       -0.031          -0.019           0.017   
                  (0.113)         (0.029)         (0.085)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.039          -0.032           0.024   
                  (0.045)         (0.026)         (0.052)   
age                 0.006          -0.002           0.018   
                  (0.011)         (0.002)         (0.017)   
income             -0.152           0.119           0.067   
                  (0.106)         (0.073)         (0.104)   
university          0.152          -0.005          -0.110   
                  (0.121)         (0.040)         (0.083)   
_cons              -0.184          -0.066          -0.351   
                  (0.402)         (0.108)         (0.439)   
------------------------------------------------------------
r2_w                0.013           0.011           0.007   
r2_b                0.225           0.123           0.106   
r2_o                0.027           0.017           0.010   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2 pho_order female age income 
&gt; university if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.041**         0.064**        -0.012   
                  (0.015)         (0.025)         (0.008)   
ideo_right2         0.164           0.529*         -0.098   
                  (0.205)         (0.240)         (0.072)   
c.neg#c.id~2       -0.054          -0.094*          0.025   
                  (0.037)         (0.046)         (0.014)   
pho_order           0.001          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.017          -0.018           0.015   
                  (0.046)         (0.033)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.027          -0.052          -0.047   
                  (0.066)         (0.080)         (0.044)   
university         -0.027          -0.035           0.002   
                  (0.041)         (0.049)         (0.014)   
_cons              -0.138          -0.212           0.060   
                  (0.110)         (0.148)         (0.052)   
------------------------------------------------------------
r2_w                0.020           0.016           0.006   
r2_b                0.111           0.129           0.119   
r2_o                0.026           0.021           0.008   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.007           0.014           0.014   
                  (0.014)         (0.015)         (0.010)   
ideo_right2        -0.146           0.096           0.048   
                  (0.160)         (0.201)         (0.129)   
c.neg#c.id~2        0.017          -0.028          -0.012   
                  (0.031)         (0.039)         (0.025)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.059           0.052           0.004   
                  (0.032)         (0.031)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income              0.003          -0.079           0.047   
                  (0.083)         (0.061)         (0.045)   
university          0.023          -0.054           0.019   
                  (0.033)         (0.041)         (0.023)   
_cons              -0.146          -0.007          -0.074   
                  (0.095)         (0.099)         (0.070)   
------------------------------------------------------------
r2_w                0.009           0.002           0.002   
r2_b                0.209           0.151           0.033   
r2_o                0.021           0.010           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
.         
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.014           0.009   
                  (0.002)         (0.011)         (0.012)   
ideo_right~x        0.007           0.053          -0.061   
                  (0.016)         (0.078)         (0.093)   
c.neg#c.id~x       -0.001          -0.008           0.003   
                  (0.003)         (0.015)         (0.017)   
pho_order           0.002***        0.006*          0.006*  
                  (0.000)         (0.002)         (0.003)   
female              0.012          -0.030           0.055   
                  (0.007)         (0.037)         (0.058)   
age                -0.000          -0.002           0.000   
                  (0.000)         (0.004)         (0.002)   
income             -0.018          -0.093          -0.141   
                  (0.015)         (0.078)         (0.116)   
university          0.007           0.007           0.124*  
                  (0.007)         (0.038)         (0.062)   
_cons              -0.054**        -0.048          -0.158   
                  (0.019)         (0.117)         (0.137)   
------------------------------------------------------------
r2_w                0.003           0.013           0.014   
r2_b                0.015           0.173           0.249   
r2_o                0.003           0.018           0.033   
N               15244.000         623.000         513.000   
N_g               803.000          33.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.006          -0.000           0.011   
                  (0.012)         (0.010)         (0.006)   
ideo_right~x       -0.019          -0.002           0.027   
                  (0.090)         (0.075)         (0.050)   
c.neg#c.id~x        0.004           0.013          -0.010   
                  (0.017)         (0.014)         (0.009)   
pho_order           0.002           0.002           0.003*  
                  (0.003)         (0.003)         (0.001)   
female              0.024           0.034          -0.068*  
                  (0.042)         (0.035)         (0.027)   
age                -0.001           0.002          -0.000   
                  (0.002)         (0.004)         (0.001)   
income              0.034          -0.011           0.042   
                  (0.118)         (0.095)         (0.061)   
university         -0.041           0.010          -0.012   
                  (0.040)         (0.052)         (0.028)   
_cons              -0.028          -0.126          -0.085   
                  (0.103)         (0.128)         (0.065)   
------------------------------------------------------------
r2_w                0.002           0.002           0.014   
r2_b                0.100           0.108           0.201   
r2_o                0.005           0.007           0.030   
N                 684.000        1045.000         665.000   
N_g                36.000          55.000          35.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.023*          0.009          -0.001          -0.005   
                  (0.010)         (0.006)         (0.008)         (0.012)   
ideo_right~x        0.046          -0.004           0.039          -0.011   
                  (0.071)         (0.044)         (0.056)         (0.081)   
c.neg#c.id~x       -0.005          -0.007          -0.007           0.008   
                  (0.014)         (0.008)         (0.011)         (0.015)   
pho_order           0.005*          0.003*          0.001           0.001   
                  (0.002)         (0.001)         (0.002)         (0.002)   
female              0.018           0.015           0.026           0.006   
                  (0.031)         (0.022)         (0.025)         (0.041)   
age                 0.001          -0.000          -0.001          -0.001   
                  (0.002)         (0.001)         (0.002)         (0.004)   
income             -0.050          -0.022          -0.021          -0.062   
                  (0.074)         (0.043)         (0.056)         (0.077)   
university          0.073*         -0.031           0.023           0.011   
                  (0.030)         (0.023)         (0.028)         (0.060)   
_cons              -0.240**        -0.032           0.007           0.039   
                  (0.090)         (0.055)         (0.068)         (0.139)   
----------------------------------------------------------------------------
r2_w                0.015           0.007           0.002           0.001   
r2_b                0.259           0.109           0.068           0.070   
r2_o                0.023           0.014           0.004           0.004   
N                 969.000        1121.000         911.000         456.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.001           0.009           0.016   
                  (0.013)         (0.007)         (0.016)   
ideo_right~x        0.115           0.029          -0.024   
                  (0.092)         (0.052)         (0.116)   
c.neg#c.id~x       -0.023          -0.007           0.010   
                  (0.018)         (0.010)         (0.023)   
pho_order           0.007**         0.004*         -0.003   
                  (0.003)         (0.002)         (0.003)   
female             -0.032          -0.032           0.022   
                  (0.045)         (0.026)         (0.052)   
age                 0.006          -0.002           0.017   
                  (0.011)         (0.002)         (0.016)   
income             -0.132           0.117           0.064   
                  (0.105)         (0.072)         (0.103)   
university          0.133          -0.004          -0.104   
                  (0.121)         (0.042)         (0.083)   
_cons              -0.287          -0.060          -0.305   
                  (0.242)         (0.103)         (0.370)   
------------------------------------------------------------
r2_w                0.016           0.011           0.007   
r2_b                0.206           0.119           0.104   
r2_o                0.028           0.017           0.011   
N                 589.000         703.000         684.000   
N_g                31.000          37.000          36.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.ideo_right2_dichox pho_order female age 
&gt; income university if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; , re 
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.018           0.033***       -0.005   
                  (0.010)         (0.010)         (0.004)   
ideo_right~x       -0.042           0.158*         -0.055   
                  (0.079)         (0.072)         (0.031)   
c.neg#c.id~x        0.007          -0.036**         0.013*  
                  (0.014)         (0.014)         (0.006)   
pho_order           0.002          -0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
female              0.031          -0.008           0.015   
                  (0.047)         (0.031)         (0.014)   
age                -0.001          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income              0.032          -0.055          -0.045   
                  (0.067)         (0.080)         (0.043)   
university         -0.033          -0.040           0.002   
                  (0.041)         (0.049)         (0.014)   
_cons              -0.061          -0.031           0.032   
                  (0.096)         (0.097)         (0.041)   
------------------------------------------------------------
r2_w                0.017           0.020           0.008   
r2_b                0.094           0.102           0.117   
r2_o                0.022           0.024           0.010   
N                 608.000         608.000         912.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.008           0.007           0.009   
                  (0.010)         (0.009)         (0.006)   
ideo_right~x       -0.112          -0.011          -0.013   
                  (0.069)         (0.066)         (0.050)   
c.neg#c.id~x        0.012          -0.006           0.002   
                  (0.013)         (0.013)         (0.010)   
pho_order          -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
female              0.059           0.048           0.004   
                  (0.031)         (0.030)         (0.022)   
age                 0.002          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
income              0.030          -0.072           0.048   
                  (0.085)         (0.058)         (0.045)   
university          0.018          -0.059           0.019   
                  (0.033)         (0.040)         (0.023)   
_cons              -0.157           0.031          -0.051   
                  (0.084)         (0.078)         (0.057)   
------------------------------------------------------------
r2_w                0.010           0.002           0.002   
r2_b                0.279           0.186           0.033   
r2_o                0.026           0.012           0.003   
N                 586.000         907.000        2641.000   
N_g                31.000          48.000         139.000   
------------------------------------------------------------
. * Table A8 Row 2
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(56,936 real changes made, 17,708 to missing)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 , re 
.   estimates store A
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1, re 
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if stimtype==&quot;single video&quot; &amp; local==0 &amp; political_interest_dichox==1, re 
.   estimates store C
.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.017           0.001          -0.049   
                  (0.022)         (0.026)         (0.029)   
wp_right2           0.063           0.050           0.079   
                  (0.052)         (0.058)         (0.067)   
c.neg#c.wp~2        0.045           0.073           0.152*  
                  (0.048)         (0.055)         (0.064)   
vid_order          -0.074***       -0.073***       -0.072***
                  (0.005)         (0.007)         (0.007)   
female             -0.027          -0.027          -0.040   
                  (0.023)         (0.031)         (0.033)   
age                 0.001           0.001          -0.000   
                  (0.001)         (0.001)         (0.001)   
income              0.016           0.112          -0.061   
                  (0.049)         (0.063)         (0.069)   
university         -0.021          -0.023          -0.058   
                  (0.025)         (0.033)         (0.037)   
_cons               0.215***        0.157*          0.306***
                  (0.055)         (0.072)         (0.077)   
------------------------------------------------------------
r2_w                0.050           0.049           0.047   
r2_b                0.037           0.042           0.052   
r2_o                0.046           0.047           0.047   
N                4665.000        2525.000        2220.000   
N_g               933.000         505.000         444.000   
------------------------------------------------------------
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store G
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.225          -0.015          -0.112   
                  (0.200)         (0.157)         (0.069)   
wp_right2          -0.387          -0.062          -0.164   
                  (0.396)         (0.854)         (0.194)   
c.neg#c.wp~2        0.325           0.601           0.147   
                  (0.416)         (0.422)         (0.177)   
vid_order          -0.117*         -0.253***       -0.069** 
                  (0.047)         (0.050)         (0.022)   
female             -0.076           0.368          -0.000   
                  (0.244)         (0.402)         (0.129)   
age                 0.014           0.081           0.000   
                  (0.018)         (0.076)         (0.004)   
income              0.119          -0.473           0.450   
                  (0.640)         (0.841)         (0.231)   
university         -0.024          -0.138          -0.101   
                  (0.235)         (0.649)         (0.114)   
_cons               0.337          -0.855           0.090   
                  (0.588)         (1.750)         (0.268)   
------------------------------------------------------------
r2_w                0.078           0.339           0.152   
r2_b                0.502           0.179           0.384   
r2_o                0.109           0.280           0.222   
N                  85.000          80.000          80.000   
N_g                17.000          16.000          16.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.088          -0.090          -0.033   
                  (0.127)         (0.194)         (0.075)   
wp_right2           0.873           0.049          -0.018   
                  (0.524)         (0.429)         (0.228)   
c.neg#c.wp~2       -0.080           0.240           0.250   
                  (0.314)         (0.374)         (0.191)   
vid_order          -0.140***       -0.112***       -0.051*  
                  (0.038)         (0.027)         (0.021)   
female              0.152          -0.018          -0.016   
                  (0.246)         (0.132)         (0.098)   
age                 0.014          -0.003          -0.001   
                  (0.010)         (0.013)         (0.003)   
income              0.285           0.262           0.020   
                  (0.634)         (0.307)         (0.204)   
university          0.444          -0.196          -0.052   
                  (0.267)         (0.213)         (0.100)   
_cons              -1.030           0.565           0.226   
                  (0.636)         (0.425)         (0.237)   
------------------------------------------------------------
r2_w                0.156           0.080           0.126   
r2_b                0.415           0.183           0.064   
r2_o                0.230           0.089           0.113   
N                  95.000         210.000          90.000   
N_g                19.000          42.000          18.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.013           0.141           0.121   
                  (0.167)         (0.096)         (0.128)   
wp_right2           0.729          -0.066          -0.262   
                  (0.623)         (0.180)         (0.267)   
c.neg#c.wp~2        0.261          -0.143          -0.198   
                  (0.373)         (0.147)         (0.197)   
vid_order          -0.092*         -0.057***       -0.099***
                  (0.046)         (0.016)         (0.027)   
female             -0.363          -0.177          -0.119   
                  (0.248)         (0.093)         (0.123)   
age                -0.021          -0.001           0.008   
                  (0.012)         (0.004)         (0.010)   
income              1.086           0.113          -0.052   
                  (0.604)         (0.128)         (0.314)   
university         -0.297           0.031          -0.046   
                  (0.230)         (0.094)         (0.160)   
_cons               0.523           0.324           0.247   
                  (0.504)         (0.185)         (0.368)   
------------------------------------------------------------
r2_w                0.057           0.097           0.103   
r2_b                0.323           0.291           0.249   
r2_o                0.126           0.149           0.133   
N                 115.000         165.000         140.000   
N_g                23.000          33.000          28.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.084          -0.050          -0.008   
                  (0.084)         (0.214)         (0.057)   
wp_right2           0.525          -0.081           0.114   
                  (0.366)         (0.532)         (0.199)   
c.neg#c.wp~2        0.281           0.324          -0.001   
                  (0.259)         (0.513)         (0.186)   
vid_order          -0.082**        -0.041          -0.040*  
                  (0.027)         (0.062)         (0.018)   
female              0.075          -0.154          -0.146   
                  (0.143)         (0.264)         (0.076)   
age                 0.007           0.084          -0.001   
                  (0.024)         (0.142)         (0.020)   
income             -0.059           0.617           0.567** 
                  (0.324)         (0.917)         (0.208)   
university         -0.129          -0.077           0.352*  
                  (0.198)         (0.621)         (0.178)   
_cons              -0.099          -1.628          -0.390   
                  (0.738)         (3.123)         (0.561)   
------------------------------------------------------------
r2_w                0.049           0.012           0.058   
r2_b                0.165           0.268           0.455   
r2_o                0.079           0.035           0.151   
N                 210.000          80.000          95.000   
N_g                42.000          16.000          19.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; wp_right2_ext==1
&gt; , re  
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.036           0.004           0.084          -0.138   
                  (0.196)         (0.084)         (0.168)         (0.084)   
wp_right2          -0.185           0.215           0.139           0.024   
                  (0.625)         (0.278)         (0.282)         (0.171)   
c.neg#c.wp~2        0.062           0.158          -0.110           0.193   
                  (0.498)         (0.204)         (0.278)         (0.132)   
vid_order          -0.088          -0.059*         -0.098*         -0.029   
                  (0.051)         (0.024)         (0.040)         (0.015)   
female              0.189          -0.019           0.104           0.078   
                  (0.234)         (0.127)         (0.155)         (0.079)   
age                -0.099          -0.006           0.009           0.004   
                  (0.082)         (0.004)         (0.009)         (0.004)   
income             -0.325          -0.088           0.118           0.211   
                  (0.401)         (0.226)         (0.334)         (0.200)   
university          0.286           0.190          -0.146           0.020   
                  (0.581)         (0.152)         (0.343)         (0.079)   
_cons               2.290           0.336           0.000          -0.117   
                  (1.742)         (0.231)             (.)         (0.228)   
----------------------------------------------------------------------------
r2_w                0.037           0.058           0.082           0.048   
r2_b                0.324           0.473           0.305           0.206   
r2_o                0.089           0.121           0.115           0.087   
N                  85.000          95.000          85.000         125.000   
N_g                17.000          19.000          17.000          25.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.069          -0.179*          0.063   
                  (0.077)         (0.074)         (0.064)   
wp_right2           0.244          -0.335           0.106   
                  (0.187)         (0.251)         (0.160)   
c.neg#c.wp~2        0.182           0.417*         -0.017   
                  (0.160)         (0.201)         (0.138)   
vid_order          -0.028          -0.057*         -0.036*  
                  (0.024)         (0.022)         (0.016)   
female             -0.148          -0.087          -0.034   
                  (0.168)         (0.109)         (0.079)   
age                -0.007           0.001           0.001   
                  (0.005)         (0.004)         (0.003)   
income             -0.789**         0.373           0.124   
                  (0.271)         (0.267)         (0.156)   
university          0.112           0.020           0.099   
                  (0.111)         (0.143)         (0.083)   
_cons               0.752*          0.196          -0.071   
                  (0.322)         (0.228)         (0.174)   
------------------------------------------------------------
r2_w                0.059           0.115           0.018   
r2_b                0.547           0.124           0.036   
r2_o                0.195           0.116           0.022   
N                  75.000         120.000         495.000   
N_g                15.000          24.000          99.000   
------------------------------------------------------------
.   
.   xtset resp vid_order
       panel variable:  resp (unbalanced)
        time variable:  vid_order, 1 to 7
                delta:  1 unit
.   replace neg = v_negativity
(0 real changes made)
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;BR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store B
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.e&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store C
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store D
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store E
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;CN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store F
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;DK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store G
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.025          -0.298          -0.073   
                  (0.231)         (0.202)         (0.066)   
wp_right2          -0.004           3.571*         -0.262   
                  (0.614)         (1.615)         (0.227)   
c.neg#c.wp~2       -0.069           1.078           0.107   
                  (0.550)         (1.646)         (0.205)   
vid_order          -0.039          -0.141**        -0.043*  
                  (0.051)         (0.052)         (0.021)   
female              0.048          -0.696*         -0.048   
                  (0.243)         (0.292)         (0.113)   
age                 0.015           0.006          -0.002   
                  (0.021)         (0.028)         (0.004)   
income             -0.107           0.404           0.000   
                  (0.500)         (0.573)         (0.212)   
university          0.161           0.160          -0.057   
                  (0.259)         (0.590)         (0.115)   
_cons              -0.284          -0.191           0.361   
                  (0.616)         (1.158)         (0.243)   
------------------------------------------------------------
r2_w                0.016           0.163           0.055   
r2_b                0.058           0.730           0.077   
r2_o                0.019           0.290           0.060   
N                  95.000          55.000         125.000   
N_g                19.000          11.000          25.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.026          -0.094          -0.033   
                  (0.186)         (0.187)         (0.099)   
wp_right2           0.199           0.455           0.104   
                  (0.674)         (0.425)         (0.332)   
c.neg#c.wp~2        0.290           0.304           0.213   
                  (0.505)         (0.368)         (0.273)   
vid_order          -0.141**        -0.088***       -0.040   
                  (0.049)         (0.025)         (0.025)   
female             -0.303          -0.151          -0.004   
                  (0.333)         (0.126)         (0.159)   
age                 0.007          -0.020          -0.004   
                  (0.013)         (0.012)         (0.003)   
income             -1.522           0.220           0.583*  
                  (1.099)         (0.299)         (0.253)   
university          0.475          -0.375*          0.005   
                  (0.404)         (0.155)         (0.134)   
_cons               0.464           0.946*         -0.113   
                  (0.713)         (0.404)         (0.250)   
------------------------------------------------------------
r2_w                0.127           0.071           0.059   
r2_b                0.349           0.349           0.435   
r2_o                0.177           0.116           0.140   
N                  75.000         200.000          80.000   
N_g                15.000          40.000          16.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;FR&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store H
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;GH&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store I
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IN&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store J
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store K
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store L
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;IT&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store M
.   esttab H I J, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.193           0.214          -0.113   
                  (0.202)         (0.135)         (0.123)   
wp_right2          -1.711*         -0.058          -0.466   
                  (0.736)         (0.183)         (0.272)   
c.neg#c.wp~2        0.598          -0.286           0.256   
                  (0.457)         (0.200)         (0.185)   
vid_order          -0.095*         -0.045**        -0.117***
                  (0.042)         (0.016)         (0.022)   
female             -0.033          -0.128          -0.096   
                  (0.243)         (0.078)         (0.172)   
age                 0.015           0.005          -0.000   
                  (0.011)         (0.005)         (0.008)   
income              0.160           0.243*         -0.162   
                  (0.446)         (0.124)         (0.294)   
university         -0.178          -0.054          -0.092   
                  (0.233)         (0.075)         (0.142)   
_cons               0.760          -0.009           0.817*  
                  (0.494)         (0.242)         (0.327)   
------------------------------------------------------------
r2_w                0.106           0.072           0.217   
r2_b                0.402           0.433           0.274   
r2_o                0.177           0.153           0.231   
N                  90.000         140.000         130.000   
N_g                18.000          28.000          26.000   
------------------------------------------------------------
.   esttab K L M, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.140          -0.235           0.016   
                  (0.099)         (0.273)         (0.097)   
wp_right2           0.339           0.028          -0.058   
                  (0.511)         (0.782)         (0.396)   
c.neg#c.wp~2        0.364           0.797           0.160   
                  (0.407)         (0.751)         (0.359)   
vid_order          -0.127***       -0.034          -0.066*  
                  (0.031)         (0.053)         (0.028)   
female             -0.137           0.124          -0.197   
                  (0.169)         (0.245)         (0.119)   
age                -0.018          -0.014           0.006   
                  (0.028)         (0.051)         (0.007)   
income             -0.700*         -0.102           1.177***
                  (0.351)         (0.581)         (0.338)   
university         -0.492*         -0.233           0.406*  
                  (0.233)         (0.537)         (0.194)   
_cons               1.615           0.543          -0.655   
                  (0.829)         (1.198)         (0.390)   
------------------------------------------------------------
r2_w                0.072           0.022           0.138   
r2_b                0.263           0.053           0.723   
r2_o                0.129           0.024           0.282   
N                 235.000          95.000          65.000   
N_g                47.000          19.000          13.000   
------------------------------------------------------------
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;JP&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store N
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;NZ&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store O
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;RU&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store P
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SE&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store Q
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;SW&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store R 
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;UK&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store S
.   quietly xtreg gslmc c.neg##c.wp_right2 vid_order female age income universi
&gt; ty if country2==&quot;US&quot; &amp; stimtype==&quot;single video&quot; &amp; local==0 &amp; political_intere
&gt; st_dichox==1, re  
.   estimates store T
.   esttab N O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    gslmc           gslmc           gslmc           gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.088          -0.088           0.300          -0.124   
                  (0.257)         (0.092)         (0.230)         (0.096)   
wp_right2           0.270           0.143           0.242           0.210   
                  (0.839)         (0.272)         (0.350)         (0.219)   
c.neg#c.wp~2        0.107           0.154          -0.377           0.206   
                  (0.704)         (0.230)         (0.342)         (0.168)   
vid_order          -0.100          -0.088***       -0.083*         -0.031*  
                  (0.059)         (0.024)         (0.042)         (0.015)   
female              0.658*         -0.169           0.241           0.008   
                  (0.330)         (0.124)         (0.170)         (0.083)   
age                -0.061          -0.004           0.005           0.002   
                  (0.085)         (0.003)         (0.007)         (0.004)   
income              0.566           0.124           0.100           0.442   
                  (0.617)         (0.240)         (0.397)         (0.271)   
university          1.076          -0.051          -0.225           0.053   
                  (2.170)         (0.141)         (0.338)         (0.086)   
_cons               0.000           0.488          -0.021          -0.261   
                      (.)         (0.268)         (0.526)         (0.285)   
----------------------------------------------------------------------------
r2_w                0.036           0.170           0.071           0.045   
r2_b                0.503           0.391           0.620           0.203   
r2_o                0.114           0.209           0.133           0.084   
N                  85.000         100.000          80.000         135.000   
N_g                17.000          20.000          16.000          27.000   
----------------------------------------------------------------------------
.   esttab R S T, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                    gslmc           gslmc           gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.042          -0.043          -0.010   
                  (0.088)         (0.091)         (0.073)   
wp_right2           0.021          -0.293           0.139   
                  (0.239)         (0.371)         (0.206)   
c.neg#c.wp~2        0.114           0.173           0.065   
                  (0.213)         (0.282)         (0.173)   
vid_order          -0.013          -0.073**        -0.032   
                  (0.028)         (0.023)         (0.018)   
female              0.214           0.017          -0.037   
                  (0.162)         (0.125)         (0.081)   
age                 0.003          -0.003           0.003   
                  (0.004)         (0.006)         (0.003)   
income             -0.754*          0.058          -0.345*  
                  (0.313)         (0.333)         (0.167)   
university         -0.145          -0.171           0.238*  
                  (0.132)         (0.159)         (0.095)   
_cons               0.382           0.451          -0.038   
                  (0.280)         (0.305)         (0.182)   
------------------------------------------------------------
r2_w                0.021           0.153           0.009   
r2_b                0.760           0.209           0.215   
r2_o                0.207           0.161           0.065   
N                  55.000          80.000         300.000   
N_g                11.000          16.000          60.000   
------------------------------------------------------------
.       
.          
. * Table A8 Row 5
.                                   
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(56,936 real changes made, 39,228 to missing)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; , re 
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; political_interest_dichox==1, re 
.   estimates store C
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.008*          0.010*  
                  (0.003)         (0.004)         (0.005)   
wp_right2           0.050           0.022           0.048   
                  (0.037)         (0.041)         (0.050)   
c.neg#c.wp~2       -0.012          -0.006          -0.011   
                  (0.007)         (0.008)         (0.010)   
pho_order           0.002***        0.003***        0.002** 
                  (0.000)         (0.001)         (0.001)   
female              0.012           0.012           0.028** 
                  (0.007)         (0.009)         (0.011)   
age                -0.000          -0.000          -0.001   
                  (0.000)         (0.000)         (0.000)   
income             -0.018          -0.021          -0.032   
                  (0.015)         (0.019)         (0.022)   
university          0.006           0.010           0.014   
                  (0.007)         (0.010)         (0.011)   
_cons              -0.070**        -0.058*         -0.063   
                  (0.023)         (0.028)         (0.032)   
------------------------------------------------------------
r2_w                0.003           0.003           0.002   
r2_b                0.015           0.022           0.046   
r2_o                0.003           0.003           0.005   
N               15263.000        8184.000        7139.000   
N_g               804.000         431.000         376.000   
------------------------------------------------------------
.         
.         
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re  
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, r
&gt; e  
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.008*          0.012           0.008   
                  (0.004)         (0.023)         (0.018)   
wp_right2           0.022          -0.081           0.056   
                  (0.041)         (0.259)         (0.254)   
c.neg#c.wp~2       -0.006          -0.001           0.008   
                  (0.008)         (0.049)         (0.044)   
pho_order           0.003***        0.008*          0.004   
                  (0.001)         (0.004)         (0.004)   
female              0.012          -0.005           0.008   
                  (0.009)         (0.089)         (0.104)   
age                -0.000          -0.002           0.001   
                  (0.000)         (0.007)         (0.003)   
income             -0.021           0.033          -0.171   
                  (0.019)         (0.171)         (0.184)   
university          0.010          -0.016           0.128   
                  (0.010)         (0.064)         (0.091)   
_cons              -0.058*         -0.119          -0.178   
                  (0.028)         (0.227)         (0.213)   
------------------------------------------------------------
r2_w                0.003           0.022           0.007   
r2_b                0.022           0.162           0.288   
r2_o                0.003           0.025           0.033   
N                8184.000         302.000         304.000   
N_g               431.000          16.000          16.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.006          -0.010          -0.005   
                  (0.014)         (0.027)         (0.011)   
wp_right2          -0.177          -0.163          -0.109   
                  (0.191)         (0.285)         (0.149)   
c.neg#c.wp~2        0.036           0.029           0.010   
                  (0.035)         (0.053)         (0.028)   
pho_order           0.001           0.002           0.004*  
                  (0.003)         (0.003)         (0.002)   
female             -0.028           0.068          -0.073*  
                  (0.050)         (0.045)         (0.031)   
age                -0.000          -0.000          -0.001   
                  (0.002)         (0.004)         (0.001)   
income              0.002           0.107          -0.008   
                  (0.127)         (0.114)         (0.065)   
university         -0.015           0.041          -0.018   
                  (0.054)         (0.073)         (0.032)   
_cons               0.063          -0.079           0.061   
                  (0.144)         (0.193)         (0.088)   
------------------------------------------------------------
r2_w                0.004           0.001           0.012   
r2_b                0.062           0.148           0.412   
r2_o                0.005           0.008           0.029   
N                 361.000         779.000         342.000   
N_g                19.000          41.000          18.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, r
&gt; e  
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, r
&gt; e  
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.022           0.015           0.009           0.003   
                  (0.016)         (0.015)         (0.021)         (0.014)   
wp_right2           0.190          -0.034           0.080          -0.052   
                  (0.211)         (0.119)         (0.168)         (0.226)   
c.neg#c.wp~2       -0.027          -0.009          -0.020          -0.013   
                  (0.037)         (0.023)         (0.032)         (0.033)   
pho_order           0.007*          0.002           0.001           0.003   
                  (0.003)         (0.002)         (0.003)         (0.002)   
female              0.006           0.062*          0.017          -0.051   
                  (0.049)         (0.028)         (0.039)         (0.043)   
age                 0.001           0.001          -0.002          -0.011   
                  (0.002)         (0.001)         (0.003)         (0.007)   
income             -0.043          -0.046           0.029          -0.118   
                  (0.120)         (0.039)         (0.104)         (0.105)   
university          0.077          -0.031          -0.014           0.022   
                  (0.046)         (0.029)         (0.050)         (0.056)   
_cons              -0.287*         -0.073          -0.018           0.308   
                  (0.124)         (0.090)         (0.153)         (0.263)   
----------------------------------------------------------------------------
r2_w                0.021           0.009           0.001           0.009   
r2_b                0.354           0.395           0.042           0.423   
r2_o                0.031           0.033           0.002           0.037   
N                 437.000         627.000         512.000         266.000   
N_g                23.000          33.000          27.000          14.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.052*          0.005           0.032   
                  (0.021)         (0.011)         (0.030)   
wp_right2          -0.255          -0.022           0.126   
                  (0.253)         (0.184)         (0.399)   
c.neg#c.wp~2        0.066          -0.003          -0.018   
                  (0.048)         (0.036)         (0.074)   
pho_order           0.011**         0.003          -0.000   
                  (0.004)         (0.002)         (0.005)   
female             -0.116          -0.032           0.026   
                  (0.061)         (0.033)         (0.080)   
age                 0.049          -0.005           0.028   
                  (0.033)         (0.009)         (0.028)   
income              0.115           0.075          -0.048   
                  (0.213)         (0.090)         (0.138)   
university         -0.835           0.022           0.054   
                  (0.671)         (0.076)         (0.200)   
_cons               0.000           0.042          -0.719   
                      (.)         (0.246)         (0.617)   
------------------------------------------------------------
r2_w                0.057           0.007           0.008   
r2_b                0.331           0.163           0.307   
r2_o                0.081           0.013           0.014   
N                 285.000         361.000         323.000   
N_g                15.000          19.000          17.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; wp_right2_ext==1, re 
&gt;  
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.060***        0.059**        -0.007   
                  (0.017)         (0.022)         (0.012)   
wp_right2           0.323           0.428*         -0.074   
                  (0.236)         (0.188)         (0.094)   
c.neg#c.wp~2       -0.101*         -0.075*          0.014   
                  (0.042)         (0.036)         (0.018)   
pho_order          -0.003           0.002           0.001   
                  (0.003)         (0.003)         (0.001)   
female              0.010          -0.065           0.017   
                  (0.062)         (0.050)         (0.020)   
age                 0.001          -0.004          -0.000   
                  (0.002)         (0.003)         (0.001)   
income              0.109          -0.140          -0.028   
                  (0.111)         (0.106)         (0.051)   
university         -0.137          -0.181           0.001   
                  (0.075)         (0.145)         (0.020)   
_cons              -0.202           0.000           0.020   
                  (0.140)             (.)         (0.080)   
------------------------------------------------------------
r2_w                0.037           0.025           0.004   
r2_b                0.382           0.301           0.150   
r2_o                0.055           0.037           0.006   
N                 361.000         323.000         475.000   
N_g                19.000          17.000          25.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.003           0.009           0.004   
                  (0.015)         (0.010)         (0.012)   
wp_right2          -0.139           0.110           0.068   
                  (0.169)         (0.136)         (0.140)   
c.neg#c.wp~2        0.030          -0.025          -0.010   
                  (0.032)         (0.026)         (0.027)   
pho_order          -0.000           0.001           0.002   
                  (0.003)         (0.002)         (0.002)   
female              0.006           0.010           0.025   
                  (0.075)         (0.030)         (0.029)   
age                -0.001          -0.000          -0.001   
                  (0.002)         (0.001)         (0.001)   
income             -0.033          -0.105           0.015   
                  (0.121)         (0.073)         (0.059)   
university          0.017          -0.020           0.029   
                  (0.049)         (0.039)         (0.031)   
_cons               0.044          -0.002          -0.061   
                  (0.160)         (0.080)         (0.082)   
------------------------------------------------------------
r2_w                0.011           0.004           0.001   
r2_b                0.373           0.201           0.050   
r2_o                0.014           0.010           0.003   
N                 284.000         455.000        1387.000   
N_g                15.000          24.000          73.000   
------------------------------------------------------------
.                             
.   xtset resp pho_order
       panel variable:  resp (unbalanced)
        time variable:  pho_order, 2 to 26
                delta:  1 unit
.   replace neg = p_negativity
(0 real changes made)
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if stimtype==&quot;single photo&quot; &amp; political_interest_dichox==1, re  
.   estimates store A
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;BR&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store B
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CA.f&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_
&gt; dichox==1, re  
.   estimates store D
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CH&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store E
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;CN&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store F
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;DK&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store G
.   esttab A B D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.008           0.006   
                  (0.005)         (0.023)         (0.014)   
wp_right2           0.048           0.027           0.003   
                  (0.050)         (0.300)         (0.241)   
c.neg#c.wp~2       -0.011          -0.014           0.022   
                  (0.010)         (0.056)         (0.044)   
pho_order           0.002**         0.007*          0.006*  
                  (0.001)         (0.003)         (0.003)   
female              0.028**        -0.023           0.079   
                  (0.011)         (0.061)         (0.068)   
age                -0.001          -0.003           0.000   
                  (0.000)         (0.005)         (0.002)   
income             -0.032          -0.088          -0.146   
                  (0.022)         (0.133)         (0.127)   
university          0.014          -0.009           0.109   
                  (0.011)         (0.068)         (0.069)   
_cons              -0.063           0.014          -0.190   
                  (0.032)         (0.190)         (0.151)   
------------------------------------------------------------
r2_w                0.002           0.014           0.016   
r2_b                0.046           0.193           0.224   
r2_o                0.005           0.019           0.033   
N                7139.000         341.000         475.000   
N_g               376.000          18.000          25.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.005          -0.020           0.002   
                  (0.025)         (0.027)         (0.011)   
wp_right2          -0.289          -0.354          -0.239   
                  (0.362)         (0.291)         (0.169)   
c.neg#c.wp~2        0.054           0.054           0.044   
                  (0.069)         (0.054)         (0.031)   
pho_order          -0.000           0.003           0.002   
                  (0.004)         (0.003)         (0.002)   
female              0.105           0.097*         -0.031   
                  (0.088)         (0.045)         (0.043)   
age                 0.001           0.001          -0.001   
                  (0.003)         (0.004)         (0.001)   
income              0.158           0.145           0.039   
                  (0.288)         (0.116)         (0.068)   
university         -0.084           0.060          -0.022   
                  (0.104)         (0.055)         (0.037)   
_cons              -0.132          -0.095           0.016   
                  (0.215)         (0.191)         (0.083)   
------------------------------------------------------------
r2_w                0.009           0.004           0.029   
r2_b                0.312           0.229           0.446   
r2_o                0.016           0.016           0.036   
N                 285.000         741.000         304.000   
N_g                15.000          39.000          16.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;FR&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store H
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;GH&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store I
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IN&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store J
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.j&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_
&gt; dichox==1, re  
.   estimates store K
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IS.p&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_
&gt; dichox==1, re  
.   estimates store L
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;IT&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store M
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;JP&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store N
.   esttab H I J K, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.038           0.027          -0.019           0.003   
                  (0.025)         (0.023)         (0.025)         (0.023)   
wp_right2           0.303           0.090          -0.115          -0.167   
                  (0.324)         (0.179)         (0.195)         (0.528)   
c.neg#c.wp~2       -0.039          -0.036           0.012           0.093   
                  (0.059)         (0.035)         (0.038)         (0.088)   
pho_order           0.002           0.004*          0.001          -0.004   
                  (0.003)         (0.002)         (0.003)         (0.005)   
female              0.004           0.066           0.026          -0.088   
                  (0.060)         (0.035)         (0.054)         (0.176)   
age                -0.002          -0.001          -0.003           0.005   
                  (0.003)         (0.002)         (0.002)         (0.011)   
income             -0.112          -0.065          -0.059          -0.060   
                  (0.110)         (0.056)         (0.093)         (0.183)   
university          0.082          -0.015           0.022          -0.113   
                  (0.058)         (0.034)         (0.044)         (0.333)   
_cons              -0.181          -0.085           0.192           0.000   
                  (0.169)         (0.155)         (0.157)             (.)   
----------------------------------------------------------------------------
r2_w                0.015           0.013           0.005           0.022   
r2_b                0.362           0.352           0.138           0.213   
r2_o                0.032           0.036           0.010           0.030   
N                 342.000         532.000         475.000         171.000   
N_g                18.000          28.000          25.000           9.000   
----------------------------------------------------------------------------
.   esttab L M N, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.075*          0.002           0.050   
                  (0.030)         (0.017)         (0.035)   
wp_right2          -0.832           0.043           0.412   
                  (0.448)         (0.330)         (0.512)   
c.neg#c.wp~2        0.156          -0.003          -0.114   
                  (0.081)         (0.063)         (0.095)   
pho_order           0.006           0.007*         -0.006   
                  (0.004)         (0.003)         (0.005)   
female             -0.056          -0.051           0.128   
                  (0.077)         (0.048)         (0.108)   
age                 0.004          -0.003           0.011   
                  (0.016)         (0.003)         (0.028)   
income             -0.263           0.101           0.127   
                  (0.183)         (0.136)         (0.203)   
university          0.380          -0.037          -0.399   
                  (0.377)         (0.079)         (0.724)   
_cons               0.000          -0.045           0.000   
                      (.)         (0.173)             (.)   
------------------------------------------------------------
r2_w                0.032           0.026           0.011   
r2_b                0.224           0.705           0.320   
r2_o                0.050           0.041           0.018   
N                 342.000         247.000         323.000   
N_g                18.000          13.000          17.000   
------------------------------------------------------------
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;NZ&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store O
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;RU&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store P
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SE&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store Q
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;SW&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store R 
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;UK&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store S
.   quietly xtreg p_gslmc_all c.neg##c.wp_right2 pho_order female age income un
&gt; iversity if country2==&quot;US&quot; &amp; stimtype==&quot;single photo&quot; &amp; political_interest_di
&gt; chox==1, re  
.   estimates store T
.   esttab O P Q, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.022           0.077**        -0.008   
                  (0.014)         (0.028)         (0.014)   
wp_right2           0.186           0.501*         -0.061   
                  (0.189)         (0.214)         (0.125)   
c.neg#c.wp~2       -0.048          -0.101*          0.020   
                  (0.036)         (0.042)         (0.024)   
pho_order           0.003          -0.002           0.002   
                  (0.002)         (0.003)         (0.001)   
female              0.005           0.035           0.007   
                  (0.044)         (0.050)         (0.022)   
age                -0.002          -0.002          -0.000   
                  (0.001)         (0.002)         (0.001)   
income             -0.037          -0.137          -0.015   
                  (0.084)         (0.116)         (0.073)   
university          0.045          -0.022          -0.001   
                  (0.050)         (0.099)         (0.023)   
_cons              -0.064          -0.257           0.011   
                  (0.115)         (0.194)         (0.100)   
------------------------------------------------------------
r2_w                0.011           0.026           0.008   
r2_b                0.274           0.295           0.060   
r2_o                0.021           0.036           0.008   
N                 380.000         304.000         513.000   
N_g                20.000          16.000          27.000   
------------------------------------------------------------
.   esttab R S T , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
              p_gslmc_all     p_gslmc_all     p_gslmc_all   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009          -0.005           0.020   
                  (0.014)         (0.012)         (0.018)   
wp_right2          -0.149          -0.002           0.187   
                  (0.182)         (0.183)         (0.247)   
c.neg#c.wp~2        0.007          -0.001          -0.023   
                  (0.035)         (0.033)         (0.045)   
pho_order          -0.001           0.004          -0.001   
                  (0.003)         (0.002)         (0.003)   
female              0.004           0.013           0.041   
                  (0.060)         (0.036)         (0.048)   
age                 0.002           0.000          -0.002   
                  (0.002)         (0.002)         (0.002)   
income              0.051          -0.034          -0.023   
                  (0.115)         (0.095)         (0.107)   
university         -0.027          -0.033           0.038   
                  (0.048)         (0.046)         (0.057)   
_cons              -0.093          -0.026          -0.079   
                  (0.118)         (0.103)         (0.133)   
------------------------------------------------------------
r2_w                0.009           0.016           0.003   
r2_b                0.464           0.111           0.060   
r2_o                0.020           0.019           0.007   
N                 208.000         301.000         836.000   
N_g                11.000          16.000          44.000   
------------------------------------------------------------
.   </code></pre>
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</div>
<div id="analysis-of-time-series-data-videos.dta" class="section level2">
<h2>Analysis of Time-series-data-videos.dta</h2>
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<pre class="r"><code>
coefs &lt;- as.data.frame(countries)
coefs$b &lt;- NA
coefs$se &lt;- NA

#V$neg &lt;- V$negativity
A &lt;- V[V$period==2 &amp; V$local==0,]

Pd &lt;- pdata.frame(A,index = c(&quot;resp&quot;, &quot;timesec&quot;))
Pd$Lgslmc &lt;- lag(Pd$gslmc,1)
Pd$Dgslmc &lt;- Pd$gslmc - Pd$Lgslmc
for (i in countries){
model &lt;- plm(Dgslmc ~ negativity * timesecStorylog + negativity * wp_right2  + Lgslmc 
             + female + age + income + university + order,
              data=Pd[Pd$country2==i,], model=&quot;random&quot;) 
  s &lt;- summary(model)$coef
  coefs$b[coefs$countries==i] &lt;- s[12,1]
  coefs$se[coefs$countries==i] &lt;- s[12,2]
}

coefs$low &lt;- coefs$b - (coefs$se * 1.96)
coefs$high &lt;- coefs$b + (coefs$se * 1.96)
coefs$range &lt;- as.numeric(rownames(coefs))

{
pdf(&quot;figure4.pdf&quot;, width = 10, height = 5, bg=&quot;white&quot;) 
par(mar=c(5.1,4.1,1.1,2.1))
plot(coefs$range,coefs$b,type=&quot;n&quot;,ann=F,axes=F,ylim=c(-.025,.025))
abline(h=0,lwd=1,lty=2,col=&quot;black&quot;)
arrows(coefs$range,coefs$low,coefs$range,coefs$high,angle=90,length=.05,code=3,col=&quot;gray&quot;,lwd=2,lty=1)
points(coefs$range,coefs$b,pch=15,cex=1.5)
axis(1,col=&quot;white&quot;,at=c(1:19),labels=coefs$countries,cex.axis=.8)
axis(2,las=1)
mtext(&quot;Ideological Difference in the Effect of Negativity&quot;,side=2,line=3.2)
invisible(dev.off())
}
</code></pre>
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<pre class="r"><code>
stata_src &lt;- readLines(&quot;Time-series-data-videos.do&quot;)
stata(stata_src,data.in=V)</code></pre>
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<!-- rnb-output-begin {"data":". *** Syntax for analyses of time-series video data\n. *** Use data file 'Time-series-data-videos.dta' with this syntax\n. * Table 4\n.   gen neg = .\n(1,327,271 missing values generated)\n.   replace neg = negativity\n(914,368 real changes made)\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc\n> ome university if period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc\n> ome university if wp_right2_dichox==0 & period==2 & local==0 , re \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc\n> ome university if wp_right2_dichox==1 & period==2 & local==0 , re \n.   estimates store C\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.wp_right2 order L.g\n> slmc female age income university if period==2 & local==0 , re \n.   estimates store D\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.006***        0.005***        0.005***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \ntimesecSto~g       -0.000           0.000          -0.001*         -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nc.neg#c.ti~g       -0.001***       -0.002***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)         (0.000)   \norder              -0.000***       -0.000***       -0.000***       -0.000***\n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.008***       -0.008***       -0.008***\n                  (0.000)         (0.000)         (0.000)         (0.000)   \nfemale             -0.001*         -0.001*         -0.000          -0.001*  \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nage                 0.000**         0.000*          0.000*          0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000          -0.000           0.001           0.000   \n                  (0.001)         (0.001)         (0.001)         (0.001)   \nuniversity         -0.000          -0.001          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)         (0.000)   \nneg                                                                 0.000   \n                                                                      (.)   \nwp_right2                                                           0.001   \n                                                                  (0.001)   \nc.neg#c.wp~2                                                        0.001   \n                                                                  (0.001)   \n_cons               0.001          -0.000           0.002           0.001   \n                  (0.001)         (0.001)         (0.001)         (0.001)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.005           0.005           0.005   \nr2_b                0.214           0.218           0.206           0.211   \nr2_o                0.003           0.003           0.003           0.003   \nN              666526.000      335833.000      330693.000      666526.000   \nN_g               933.000         471.000         462.000         933.000   \n----------------------------------------------------------------------------\n.   \n.   \n. * Figure 4\n.   \n.   gen right2 = .\n(1,327,271 missing values generated)\n.   replace right2= wp_right2\n(1,316,553 real changes made)\n.    \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.003           0.007           0.010** \n                  (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.002           0.000          -0.002*  \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001          -0.002*         -0.003***\n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.013*         -0.009          -0.008*  \n                  (0.005)         (0.006)         (0.004)   \nc.neg#c.ri~2        0.008           0.011*         -0.001   \n                  (0.005)         (0.005)         (0.003)   \norder              -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.009***       -0.008***       -0.017***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.001           0.000          -0.002   \n                  (0.002)         (0.002)         (0.002)   \nage                 0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.003           0.005   \n                  (0.005)         (0.004)         (0.004)   \nuniversity          0.003          -0.003          -0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.007          -0.010           0.009   \n                  (0.007)         (0.008)         (0.006)   \n------------------------------------------------------------\nr2_w                0.004           0.006           0.012   \nr2_b                0.097           0.002           0.056   \nr2_o                0.004           0.005           0.009   \nN               24315.000       23296.000       19125.000   \nN_g                35.000          32.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.005*  \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005           0.003   \n                  (0.005)         (0.006)         (0.003)   \nc.neg#c.ri~2       -0.001          -0.000           0.001   \n                  (0.004)         (0.005)         (0.002)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.000           0.005          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006***       -0.005*          0.001   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.014*          0.002          -0.003   \n                  (0.006)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.015           0.014           0.015   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.001          -0.002   \n                  (0.004)         (0.002)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005          -0.007*  \n                  (0.006)         (0.003)         (0.003)   \nc.neg#c.ri~2        0.004           0.001           0.002   \n                  (0.005)         (0.002)         (0.002)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.003***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.004*          0.000   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.003   \n                  (0.002)         (0.001)         (0.002)   \n_cons               0.019**         0.009**         0.003   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.004   \nr2_b                0.005           0.180           0.083   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42808.000       36042.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.005           0.005   \n                  (0.003)         (0.004)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001          -0.003          -0.003   \n                  (0.004)         (0.005)         (0.004)   \nc.neg#c.ri~2        0.003           0.006          -0.000   \n                  (0.003)         (0.004)         (0.004)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*         -0.000          -0.000   \n                  (0.003)         (0.005)         (0.004)   \nuniversity         -0.003          -0.000           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.023**        -0.005           0.003   \n                  (0.008)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.088           0.001           0.058   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.003           0.013**         0.001   \n                  (0.006)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.003           0.010           0.008          -0.001   \n                  (0.009)         (0.005)         (0.004)         (0.001)   \nc.neg#c.ri~2        0.005           0.003           0.001           0.001   \n                  (0.007)         (0.004)         (0.004)         (0.001)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.003           0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.010          -0.001          -0.002           0.004*  \n                  (0.005)         (0.004)         (0.005)         (0.001)   \nuniversity          0.005           0.002          -0.002          -0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.045*          0.009          -0.007           0.001   \n                  (0.021)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.091           0.072           0.000           0.045   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.010**         0.006***\n                  (0.003)         (0.003)         (0.002)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001           0.001           0.001   \n                  (0.004)         (0.004)         (0.002)   \nc.neg#c.ri~2       -0.001           0.006          -0.000   \n                  (0.003)         (0.004)         (0.002)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.008           0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.008          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.008           0.348           0.181   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.  \n. * Table A3 Row 3\n.   replace right2= wp_right2\n(0 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.003           0.007           0.010** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.001          -0.013*         -0.009          -0.008*  \n                  (0.001)         (0.005)         (0.006)         (0.004)   \nc.neg#c.ri~2        0.001           0.008           0.011*         -0.001   \n                  (0.001)         (0.005)         (0.005)         (0.003)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001           0.000          -0.002   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**         0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.002           0.003           0.005   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.003          -0.003          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.007          -0.010           0.009   \n                  (0.001)         (0.007)         (0.008)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.211           0.097           0.002           0.056   \nr2_o                0.003           0.004           0.005           0.009   \nN              666526.000       24315.000       23296.000       19125.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.005*  \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005           0.003   \n                  (0.005)         (0.006)         (0.003)   \nc.neg#c.ri~2       -0.001          -0.000           0.001   \n                  (0.004)         (0.005)         (0.002)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.000           0.005          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006***       -0.005*          0.001   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.014*          0.002          -0.003   \n                  (0.006)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.015           0.014           0.015   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.001          -0.002   \n                  (0.004)         (0.002)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005          -0.007*  \n                  (0.006)         (0.003)         (0.003)   \nc.neg#c.ri~2        0.004           0.001           0.002   \n                  (0.005)         (0.002)         (0.002)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.003***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.004*          0.000   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.003   \n                  (0.002)         (0.001)         (0.002)   \n_cons               0.019**         0.009**         0.003   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.004   \nr2_b                0.005           0.180           0.083   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42808.000       36042.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.005           0.005   \n                  (0.003)         (0.004)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001          -0.003          -0.003   \n                  (0.004)         (0.005)         (0.004)   \nc.neg#c.ri~2        0.003           0.006          -0.000   \n                  (0.003)         (0.004)         (0.004)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*         -0.000          -0.000   \n                  (0.003)         (0.005)         (0.004)   \nuniversity         -0.003          -0.000           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.023**        -0.005           0.003   \n                  (0.008)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.088           0.001           0.058   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.003           0.013**         0.001   \n                  (0.006)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.003           0.010           0.008          -0.001   \n                  (0.009)         (0.005)         (0.004)         (0.001)   \nc.neg#c.ri~2        0.005           0.003           0.001           0.001   \n                  (0.007)         (0.004)         (0.004)         (0.001)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.003           0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.010          -0.001          -0.002           0.004*  \n                  (0.005)         (0.004)         (0.005)         (0.001)   \nuniversity          0.005           0.002          -0.002          -0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.045*          0.009          -0.007           0.001   \n                  (0.021)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.091           0.072           0.000           0.045   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.010**         0.006***\n                  (0.003)         (0.003)         (0.002)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001           0.001           0.001   \n                  (0.004)         (0.004)         (0.002)   \nc.neg#c.ri~2       -0.001           0.006          -0.000   \n                  (0.003)         (0.004)         (0.002)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.008           0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.008          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.008           0.348           0.181   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==1 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==1 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==1 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==1 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==1 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==1 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==1 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.001           0.017*         -0.015           0.003   \n                  (0.001)         (0.007)         (0.011)         (0.010)   \ntimesecSto~g       -0.001*          0.000          -0.003          -0.004   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nc.neg#c.ti~g       -0.000          -0.004**         0.004          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.003)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.001          -0.031**        -0.004          -0.017*  \n                  (0.001)         (0.010)         (0.011)         (0.008)   \nc.neg#c.ri~2       -0.001          -0.001           0.011           0.009   \n                  (0.001)         (0.007)         (0.009)         (0.007)   \norder              -0.000***       -0.001          -0.001          -0.000   \n                  (0.000)         (0.000)         (0.001)         (0.000)   \nL.gslmc            -0.008***       -0.015***       -0.006***       -0.025***\n                  (0.000)         (0.002)         (0.002)         (0.003)   \nfemale             -0.000          -0.008*          0.006          -0.008   \n                  (0.001)         (0.004)         (0.005)         (0.004)   \nage                 0.000*         -0.002***        0.001           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.001           0.018*          0.004          -0.004   \n                  (0.001)         (0.009)         (0.008)         (0.008)   \nuniversity         -0.001**         0.006          -0.012           0.003   \n                  (0.001)         (0.004)         (0.006)         (0.004)   \n_cons               0.003           0.044**         0.001           0.023*  \n                  (0.002)         (0.015)         (0.017)         (0.011)   \n----------------------------------------------------------------------------\nr2_w                0.008           0.017           0.007           0.018   \nr2_b                0.208           0.001           0.032           0.121   \nr2_o                0.003           0.010           0.003           0.012   \nN              232990.000        7770.000        6336.000        5346.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.007          -0.010          -0.001   \n                  (0.008)         (0.006)         (0.002)   \ntimesecSto~g       -0.008**        -0.001          -0.001   \n                  (0.003)         (0.002)         (0.001)   \nc.neg#c.ti~g        0.003           0.002           0.000   \n                  (0.002)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.004          -0.028*         -0.003   \n                  (0.013)         (0.012)         (0.005)   \nc.neg#c.ri~2       -0.006           0.002           0.001   \n                  (0.009)         (0.007)         (0.002)   \norder              -0.000          -0.001          -0.000   \n                  (0.001)         (0.000)         (0.000)   \nL.gslmc            -0.009***       -0.007***       -0.014***\n                  (0.003)         (0.001)         (0.002)   \nfemale              0.004           0.002          -0.000   \n                  (0.004)         (0.003)         (0.002)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.001           0.000           0.003   \n                  (0.012)         (0.007)         (0.003)   \nuniversity          0.004           0.007           0.000   \n                  (0.004)         (0.004)         (0.002)   \n_cons               0.013           0.003          -0.001   \n                  (0.014)         (0.012)         (0.005)   \n------------------------------------------------------------\nr2_w                0.011           0.010           0.012   \nr2_b                0.225           0.074           0.106   \nr2_o                0.004           0.003           0.007   \nN                5004.000       10920.000        8855.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==1 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==1 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==1 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==1 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==1 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==1 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.028***        0.017***       -0.000   \n                  (0.007)         (0.003)         (0.005)   \ntimesecSto~g       -0.005*         -0.004***        0.000   \n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.008***       -0.004***       -0.000   \n                  (0.002)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.034**        -0.006           0.000   \n                  (0.012)         (0.006)         (0.004)   \nc.neg#c.ri~2       -0.009          -0.004           0.001   \n                  (0.010)         (0.003)         (0.003)   \norder              -0.001          -0.000*         -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.022***       -0.010***       -0.001   \n                  (0.002)         (0.001)         (0.001)   \nfemale             -0.010**        -0.001          -0.001   \n                  (0.004)         (0.002)         (0.002)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.004          -0.002           0.002   \n                  (0.009)         (0.003)         (0.003)   \nuniversity          0.004          -0.000          -0.002   \n                  (0.004)         (0.002)         (0.002)   \n_cons               0.044***        0.015*         -0.005   \n                  (0.013)         (0.006)         (0.006)   \n------------------------------------------------------------\nr2_w                0.016           0.015           0.001   \nr2_b                0.026           0.562           0.009   \nr2_o                0.012           0.007           0.000   \nN               14076.000       14940.000       14500.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.000           0.034***        0.012   \n                  (0.006)         (0.009)         (0.011)   \ntimesecSto~g       -0.003          -0.004*          0.002   \n                  (0.001)         (0.002)         (0.004)   \nc.neg#c.ti~g       -0.000          -0.010***       -0.003   \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.003          -0.002           0.023   \n                  (0.007)         (0.008)         (0.016)   \nc.neg#c.ri~2        0.007           0.006          -0.028*  \n                  (0.006)         (0.008)         (0.014)   \norder              -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.005***       -0.010***       -0.021***\n                  (0.001)         (0.002)         (0.003)   \nfemale              0.000           0.003           0.003   \n                  (0.002)         (0.003)         (0.003)   \nage                -0.000          -0.001          -0.001*  \n                  (0.000)         (0.001)         (0.000)   \nincome              0.003          -0.013          -0.025** \n                  (0.005)         (0.008)         (0.009)   \nuniversity         -0.006*         -0.000          -0.006   \n                  (0.003)         (0.006)         (0.005)   \n_cons               0.017           0.036           0.024   \n                  (0.013)         (0.022)         (0.019)   \n------------------------------------------------------------\nr2_w                0.006           0.007           0.017   \nr2_b                0.275           0.059           0.003   \nr2_o                0.002           0.007           0.011   \nN               18389.000        8288.000        6142.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==1 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==1 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==1 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==1 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==1 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==1 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==1 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.016          -0.023***        0.017*          0.002   \n                  (0.008)         (0.007)         (0.007)         (0.001)   \ntimesecSto~g       -0.007*         -0.010***       -0.000           0.000   \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nc.neg#c.ti~g        0.006**         0.006**        -0.003          -0.001*  \n                  (0.002)         (0.002)         (0.002)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.021          -0.018           0.011          -0.003   \n                  (0.018)         (0.013)         (0.006)         (0.002)   \nc.neg#c.ri~2       -0.004           0.009          -0.007           0.001   \n                  (0.013)         (0.007)         (0.005)         (0.001)   \norder              -0.001*         -0.000          -0.000           0.000   \n                  (0.001)         (0.001)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.034***       -0.007***        0.000   \n                  (0.002)         (0.003)         (0.001)         (0.001)   \nfemale              0.007          -0.009           0.003          -0.000   \n                  (0.004)         (0.005)         (0.003)         (0.001)   \nage                -0.002          -0.000           0.000           0.000   \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome              0.003           0.002          -0.012          -0.001   \n                  (0.008)         (0.008)         (0.007)         (0.002)   \nuniversity          0.001          -0.007           0.002          -0.001   \n                  (0.006)         (0.005)         (0.004)         (0.001)   \n_cons               0.035           0.067***       -0.011          -0.003   \n                  (0.033)         (0.015)         (0.010)         (0.003)   \n----------------------------------------------------------------------------\nr2_w                0.014           0.030           0.007           0.000   \nr2_b                0.021           0.051           0.001           0.195   \nr2_o                0.010           0.020           0.005           0.001   \nN                8064.000        6688.000        8700.000       11616.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011          -0.000           0.009***\n                  (0.006)         (0.004)         (0.002)   \ntimesecSto~g        0.001           0.002           0.002** \n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003          -0.000          -0.002***\n                  (0.002)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.004          -0.008           0.002   \n                  (0.006)         (0.006)         (0.003)   \nc.neg#c.ri~2        0.000          -0.003           0.002   \n                  (0.006)         (0.004)         (0.003)   \norder              -0.001**        -0.000          -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.009***       -0.006***\n                  (0.002)         (0.001)         (0.001)   \nfemale              0.000          -0.001          -0.000   \n                  (0.003)         (0.002)         (0.001)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.021**         0.004          -0.001   \n                  (0.008)         (0.004)         (0.002)   \nuniversity         -0.002           0.002          -0.001   \n                  (0.003)         (0.003)         (0.001)   \n_cons              -0.006          -0.011          -0.005   \n                  (0.009)         (0.007)         (0.004)   \n------------------------------------------------------------\nr2_w                0.010           0.005           0.006   \nr2_b                0.000           0.029           0.150   \nr2_o                0.007           0.004           0.003   \nN                6975.000       16176.000       54205.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.   \n.  \n. * Table A6 Row 3\n.   replace right2= wp_right2\n(0 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.003           0.007           0.010** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.001          -0.013*         -0.009          -0.008*  \n                  (0.001)         (0.005)         (0.006)         (0.004)   \nc.neg#c.ri~2        0.001           0.008           0.011*         -0.001   \n                  (0.001)         (0.005)         (0.005)         (0.003)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001           0.000          -0.002   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**         0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.002           0.003           0.005   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.003          -0.003          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.007          -0.010           0.009   \n                  (0.001)         (0.007)         (0.008)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.211           0.097           0.002           0.056   \nr2_o                0.003           0.004           0.005           0.009   \nN              666526.000       24315.000       23296.000       19125.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.005*  \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005           0.003   \n                  (0.005)         (0.006)         (0.003)   \nc.neg#c.ri~2       -0.001          -0.000           0.001   \n                  (0.004)         (0.005)         (0.002)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.000           0.005          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006***       -0.005*          0.001   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.014*          0.002          -0.003   \n                  (0.006)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.015           0.014           0.015   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.001          -0.002   \n                  (0.004)         (0.002)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005          -0.007*  \n                  (0.006)         (0.003)         (0.003)   \nc.neg#c.ri~2        0.004           0.001           0.002   \n                  (0.005)         (0.002)         (0.002)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.003***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.004*          0.000   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.003   \n                  (0.002)         (0.001)         (0.002)   \n_cons               0.019**         0.009**         0.003   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.004   \nr2_b                0.005           0.180           0.083   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42808.000       36042.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.005           0.005   \n                  (0.003)         (0.004)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001          -0.003          -0.003   \n                  (0.004)         (0.005)         (0.004)   \nc.neg#c.ri~2        0.003           0.006          -0.000   \n                  (0.003)         (0.004)         (0.004)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*         -0.000          -0.000   \n                  (0.003)         (0.005)         (0.004)   \nuniversity         -0.003          -0.000           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.023**        -0.005           0.003   \n                  (0.008)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.088           0.001           0.058   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.003           0.013**         0.001   \n                  (0.006)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.003           0.010           0.008          -0.001   \n                  (0.009)         (0.005)         (0.004)         (0.001)   \nc.neg#c.ri~2        0.005           0.003           0.001           0.001   \n                  (0.007)         (0.004)         (0.004)         (0.001)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.003           0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.010          -0.001          -0.002           0.004*  \n                  (0.005)         (0.004)         (0.005)         (0.001)   \nuniversity          0.005           0.002          -0.002          -0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.045*          0.009          -0.007           0.001   \n                  (0.021)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.091           0.072           0.000           0.045   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.010**         0.006***\n                  (0.003)         (0.003)         (0.002)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001           0.001           0.001   \n                  (0.004)         (0.004)         (0.002)   \nc.neg#c.ri~2       -0.001           0.006          -0.000   \n                  (0.003)         (0.004)         (0.002)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.008           0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.008          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.008           0.348           0.181   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.   \n.   \n.   replace right2= wp_right2_dicho2\n(1,253,906 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.005           0.009*          0.010** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.000          -0.003          -0.015***       -0.001   \n                  (0.000)         (0.002)         (0.004)         (0.002)   \nc.neg#c.ri~2        0.000           0.003           0.010***       -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.008***       -0.009***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001          -0.004          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \nage                 0.000**         0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.002           0.004           0.004   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.003          -0.002          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.002          -0.006           0.007   \n                  (0.001)         (0.007)         (0.008)         (0.005)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.210           0.019           0.000           0.107   \nr2_o                0.003           0.004           0.005           0.009   \nN              666526.000       24315.000       23296.000       19125.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.005           0.005** \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.000          -0.001           0.000   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2       -0.002           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale              0.000           0.002          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.002           0.005          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006**        -0.006*          0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons              -0.011*          0.001          -0.002   \n                  (0.005)         (0.006)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.020           0.017           0.005   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012**         0.002          -0.002   \n                  (0.004)         (0.002)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.001          -0.004**        -0.001   \n                  (0.003)         (0.002)         (0.002)   \nc.neg#c.ri~2        0.001          -0.001           0.002   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.003***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.001           0.004*          0.001   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.002   \n                  (0.002)         (0.001)         (0.002)   \n_cons               0.020**         0.010**        -0.001   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.009           0.004   \nr2_b                0.010           0.143           0.152   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42808.000       36042.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.007*          0.005   \n                  (0.003)         (0.003)         (0.002)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001          -0.001          -0.005   \n                  (0.003)         (0.002)         (0.003)   \nc.neg#c.ri~2        0.002           0.001           0.003   \n                  (0.002)         (0.002)         (0.002)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000*         -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*          0.000           0.000   \n                  (0.003)         (0.004)         (0.004)   \nuniversity         -0.003          -0.000           0.001   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.024**        -0.008           0.004   \n                  (0.007)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.087           0.003           0.035   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004           0.003           0.013***        0.001   \n                  (0.005)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.000           0.005*          0.003          -0.001** \n                  (0.004)         (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.003           0.002           0.001           0.001*  \n                  (0.003)         (0.002)         (0.002)         (0.000)   \norder              -0.001**        -0.001***       -0.000          -0.000***\n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.003           0.001          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.011*         -0.001          -0.003           0.004** \n                  (0.005)         (0.003)         (0.005)         (0.001)   \nuniversity          0.004           0.001          -0.002          -0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.048*          0.011*         -0.005           0.002   \n                  (0.019)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.007           0.012           0.009           0.002   \nr2_b                0.085           0.079           0.001           0.090   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.012***        0.006***\n                  (0.003)         (0.003)         (0.001)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.000           0.001           0.002*  \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.000           0.001          -0.001   \n                  (0.002)         (0.002)         (0.001)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.001   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.008           0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.007          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.007           0.356           0.142   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   \n.   replace right2= wp_right2_dichox\n(372,030 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.005           0.007           0.008** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.000          -0.003          -0.001          -0.003   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nc.neg#c.ri~2        0.001*          0.002           0.004*          0.002   \n                  (0.000)         (0.002)         (0.002)         (0.001)   \norder              -0.000***       -0.000          -0.001***       -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.002           0.000          -0.003   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**         0.000           0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome             -0.000           0.002           0.003           0.005   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.004          -0.004          -0.003   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.004          -0.013           0.009   \n                  (0.001)         (0.007)         (0.009)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.214           0.027           0.008           0.071   \nr2_o                0.003           0.004           0.005           0.009   \nN              666526.000       24315.000       23296.000       19125.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.005** \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.001          -0.003           0.001   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2       -0.000           0.001           0.000   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.000           0.003          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.000           0.006          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006**        -0.005*          0.000   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.012*          0.001          -0.002   \n                  (0.006)         (0.006)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.017           0.004           0.008   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011**         0.001          -0.001   \n                  (0.004)         (0.002)         (0.002)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.003          -0.000          -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ri~2        0.001           0.000           0.001   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.004***       -0.004** \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.001           0.004*          0.001   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.002          -0.002*         -0.003   \n                  (0.002)         (0.001)         (0.001)   \n_cons               0.020**         0.007*         -0.000   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.004   \nr2_b                0.004           0.218           0.094   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42808.000       36042.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.007           0.005*  \n                  (0.003)         (0.003)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001          -0.001          -0.000   \n                  (0.001)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.001           0.001          -0.001   \n                  (0.001)         (0.002)         (0.001)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.001*         -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*         -0.000          -0.001   \n                  (0.003)         (0.004)         (0.004)   \nuniversity         -0.003          -0.000           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.024***       -0.005           0.003   \n                  (0.007)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.081           0.001           0.060   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003           0.004           0.013***        0.002*  \n                  (0.005)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.002           0.003           0.002           0.000   \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nc.neg#c.ri~2        0.002          -0.001           0.002          -0.000   \n                  (0.002)         (0.002)         (0.002)         (0.000)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001          -0.005*          0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.010          -0.002          -0.002           0.003*  \n                  (0.005)         (0.003)         (0.005)         (0.001)   \nuniversity          0.005           0.002          -0.002           0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.041*          0.011*         -0.004           0.001   \n                  (0.020)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.007           0.012           0.009           0.002   \nr2_b                0.091           0.066           0.004           0.037   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.012***        0.005***\n                  (0.003)         (0.003)         (0.001)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.002           0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2       -0.001           0.000           0.001   \n                  (0.001)         (0.001)         (0.001)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000*          0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007           0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.007          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.026           0.361           0.166   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   \n.   replace right2= left_right2\n(1,239,431 real changes made, 1,364 to missing)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.008           0.006           0.010** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.001          -0.006          -0.012*         -0.010** \n                  (0.001)         (0.004)         (0.006)         (0.003)   \nc.neg#c.ri~2        0.000          -0.004           0.011*         -0.002   \n                  (0.001)         (0.003)         (0.005)         (0.003)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001           0.000          -0.002   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**        -0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.004           0.004           0.006   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.004          -0.004          -0.003   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.006          -0.008           0.013*  \n                  (0.001)         (0.007)         (0.009)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.212           0.027           0.001           0.020   \nr2_o                0.003           0.004           0.005           0.009   \nN              665849.000       24315.000       23296.000       19125.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011**         0.001           0.006** \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.007          -0.012**         0.002   \n                  (0.005)         (0.004)         (0.002)   \nc.neg#c.ri~2        0.004           0.008*         -0.002   \n                  (0.004)         (0.004)         (0.002)   \norder              -0.000*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale              0.001           0.003          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.004           0.003          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006**        -0.005           0.000   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.009           0.008          -0.003   \n                  (0.006)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.005           0.001           0.005   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.001           0.002   \n                  (0.004)         (0.002)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.007           0.003          -0.006** \n                  (0.004)         (0.002)         (0.002)   \nc.neg#c.ri~2        0.003           0.002          -0.004*  \n                  (0.004)         (0.002)         (0.002)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.004          -0.003***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.003          -0.001   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.001          -0.002   \n                  (0.002)         (0.001)         (0.001)   \n_cons               0.017*          0.005           0.004   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.009           0.004   \nr2_b                0.002           0.162           0.015   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42131.000       36042.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.010*          0.006*  \n                  (0.003)         (0.004)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.004           0.003           0.005   \n                  (0.003)         (0.004)         (0.003)   \nc.neg#c.ri~2        0.001          -0.004          -0.003   \n                  (0.002)         (0.003)         (0.003)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.003*  \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000*         -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*         -0.000          -0.001   \n                  (0.003)         (0.004)         (0.004)   \nuniversity         -0.003          -0.001           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.024***       -0.008          -0.000   \n                  (0.007)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.081           0.001           0.054   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004          -0.001           0.017***        0.002*  \n                  (0.006)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.002           0.001           0.006          -0.001   \n                  (0.008)         (0.005)         (0.006)         (0.001)   \nc.neg#c.ri~2        0.001           0.010**        -0.005           0.000   \n                  (0.008)         (0.004)         (0.005)         (0.001)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.002***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.005*          0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000** \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.011*         -0.003          -0.001           0.004** \n                  (0.005)         (0.003)         (0.005)         (0.001)   \nuniversity          0.005           0.003          -0.002           0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.052**         0.012*         -0.006           0.001   \n                  (0.019)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.084           0.108           0.007           0.073   \nr2_o                0.006           0.011           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.004           0.012**         0.006***\n                  (0.003)         (0.004)         (0.002)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.004           0.006           0.002   \n                  (0.004)         (0.005)         (0.001)   \nc.neg#c.ri~2        0.002           0.001          -0.000   \n                  (0.003)         (0.004)         (0.001)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.003*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000*          0.000           0.000** \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.006          -0.000           0.000   \n                  (0.005)         (0.003)         (0.001)   \nuniversity          0.003           0.002           0.001   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.005          -0.009***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.021           0.327           0.167   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   \n.   replace right2= left_right2_dichox\n(1,185,562 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.007           0.009*          0.009** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.000          -0.002          -0.004          -0.004** \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nc.neg#c.ri~2        0.000          -0.001           0.000           0.001   \n                  (0.000)         (0.002)         (0.002)         (0.001)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001          -0.000          -0.001   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**         0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.002           0.004           0.006   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.003          -0.004          -0.003   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.004          -0.007           0.010   \n                  (0.001)         (0.007)         (0.009)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.212           0.017           0.001           0.053   \nr2_o                0.003           0.004           0.004           0.009   \nN              665849.000       24315.000       23296.000       19125.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012**         0.005           0.005** \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.005*         -0.003           0.000   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.003           0.002          -0.001   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale              0.002           0.003          -0.001   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.006           0.005          -0.000   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006**        -0.006*          0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons              -0.009           0.001          -0.002   \n                  (0.006)         (0.006)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.000           0.006           0.005   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011**         0.001           0.000   \n                  (0.004)         (0.002)         (0.002)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000          -0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.004           0.002*         -0.004***\n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ri~2        0.001           0.001          -0.001   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.003**        -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.003          -0.000   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.001          -0.002   \n                  (0.002)         (0.001)         (0.001)   \n_cons               0.018**         0.006*          0.001   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.009           0.004   \nr2_b                0.000           0.149           0.010   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42131.000       36042.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.008*          0.005   \n                  (0.003)         (0.003)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.004**         0.001           0.001   \n                  (0.001)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.001          -0.003          -0.000   \n                  (0.001)         (0.002)         (0.001)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.005***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.006*         -0.000          -0.001   \n                  (0.003)         (0.004)         (0.004)   \nuniversity         -0.002          -0.001           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.022***       -0.007           0.001   \n                  (0.007)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.046           0.001           0.064   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004           0.001           0.016***        0.002   \n                  (0.005)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.004***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.000          -0.001           0.004*         -0.000   \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nc.neg#c.ri~2        0.001           0.004*         -0.002           0.001   \n                  (0.002)         (0.002)         (0.002)         (0.000)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.006*          0.001          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.011*         -0.003           0.000           0.003*  \n                  (0.005)         (0.003)         (0.005)         (0.001)   \nuniversity          0.005           0.003          -0.002           0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.050**         0.013*         -0.006           0.001   \n                  (0.018)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.086           0.100           0.002           0.047   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.004           0.012***        0.006***\n                  (0.003)         (0.003)         (0.001)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003           0.005**         0.001   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.002           0.001           0.000   \n                  (0.001)         (0.001)         (0.001)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.003           0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000*          0.000           0.000** \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.006          -0.002           0.000   \n                  (0.005)         (0.003)         (0.001)   \nuniversity          0.002           0.003           0.001   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.005          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.045           0.149           0.165   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   \n.   replace right2= ideo_right2\n(1,309,786 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.006           0.006           0.010** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.000          -0.010*         -0.012*         -0.010** \n                  (0.001)         (0.005)         (0.006)         (0.004)   \nc.neg#c.ri~2        0.001          -0.000           0.013*         -0.002   \n                  (0.001)         (0.004)         (0.005)         (0.003)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001           0.000          -0.002   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**        -0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.004           0.003           0.005   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.004          -0.004          -0.003   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.007          -0.008           0.011*  \n                  (0.001)         (0.007)         (0.009)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.214           0.080           0.000           0.032   \nr2_o                0.003           0.004           0.005           0.009   \nN              665849.000       24315.000       23296.000       19125.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012**         0.001           0.005** \n                  (0.004)         (0.005)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003          -0.019**         0.003   \n                  (0.006)         (0.007)         (0.003)   \nc.neg#c.ri~2        0.003           0.009          -0.001   \n                  (0.004)         (0.006)         (0.002)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale              0.000           0.003          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.003           0.004          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006**        -0.004           0.001   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.010           0.010          -0.003   \n                  (0.006)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.015           0.001           0.008   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*         -0.001           0.001   \n                  (0.005)         (0.003)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.008           0.003          -0.014***\n                  (0.005)         (0.004)         (0.004)   \nc.neg#c.ri~2        0.004           0.004          -0.003   \n                  (0.005)         (0.004)         (0.003)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.004***       -0.002   \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.004          -0.003   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.003*  \n                  (0.002)         (0.001)         (0.001)   \n_cons               0.017*          0.006           0.008   \n                  (0.007)         (0.004)         (0.005)   \n------------------------------------------------------------\nr2_w                0.009           0.009           0.004   \nr2_b                0.003           0.195           0.002   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42131.000       36042.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.004           0.007           0.006*  \n                  (0.003)         (0.007)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.008           0.007           0.003   \n                  (0.005)         (0.011)         (0.004)   \nc.neg#c.ri~2        0.006           0.000          -0.003   \n                  (0.005)         (0.010)         (0.003)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004*  \n                  (0.001)         (0.002)         (0.001)   \nage                -0.001*         -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*          0.001          -0.001   \n                  (0.003)         (0.005)         (0.004)   \nuniversity         -0.003          -0.001           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.027***       -0.011           0.001   \n                  (0.007)         (0.012)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.080           0.002           0.065   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.001           0.015**         0.002   \n                  (0.006)         (0.004)         (0.005)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.000           0.006           0.014          -0.002   \n                  (0.010)         (0.006)         (0.007)         (0.001)   \nc.neg#c.ri~2        0.004           0.008          -0.002           0.001   \n                  (0.009)         (0.004)         (0.006)         (0.001)   \norder              -0.001**        -0.001***       -0.000          -0.000***\n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.002***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.004           0.001          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000** \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.011*         -0.002          -0.000           0.004** \n                  (0.005)         (0.003)         (0.005)         (0.001)   \nuniversity          0.005           0.002          -0.002          -0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.049*          0.010          -0.009           0.001   \n                  (0.021)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.089           0.103           0.000           0.076   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.004           0.011**         0.006***\n                  (0.003)         (0.004)         (0.002)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003           0.004           0.002   \n                  (0.004)         (0.005)         (0.002)   \nc.neg#c.ri~2        0.001           0.005          -0.000   \n                  (0.003)         (0.004)         (0.002)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000** \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007          -0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.006          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.013           0.333           0.173   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   \n.   replace right2= ideo_right2_dichox\n(1,309,786 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.007           0.008*          0.009** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.001*         -0.003          -0.003          -0.004** \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nc.neg#c.ri~2        0.001***       -0.002           0.003           0.001   \n                  (0.000)         (0.002)         (0.002)         (0.001)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001           0.001          -0.001   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**         0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.001           0.002           0.005   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.004          -0.003          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.004          -0.010           0.009   \n                  (0.001)         (0.007)         (0.009)         (0.005)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.207           0.012           0.000           0.032   \nr2_o                0.003           0.004           0.004           0.009   \nN              665849.000       24315.000       23296.000       19125.000   \nN_g               932.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012**         0.006           0.005*  \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.006**        -0.005**         0.001   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.002           0.001           0.001   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale              0.002           0.003          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.008           0.006          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.005**        -0.005*          0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons              -0.009           0.004          -0.002   \n                  (0.005)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.002           0.003           0.017   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011**         0.001           0.000   \n                  (0.004)         (0.002)         (0.002)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.004           0.001          -0.005***\n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ri~2        0.001           0.001          -0.001   \n                  (0.002)         (0.001)         (0.001)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.004***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.004*         -0.003   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.003   \n                  (0.002)         (0.001)         (0.001)   \n_cons               0.018**         0.007*          0.000   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.009           0.004   \nr2_b                0.000           0.195           0.002   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42131.000       36042.000   \nN_g                51.000          59.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.007*          0.005   \n                  (0.003)         (0.004)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003*          0.000           0.001   \n                  (0.001)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.001           0.000          -0.000   \n                  (0.001)         (0.002)         (0.001)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004*  \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000*         -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*          0.000          -0.001   \n                  (0.003)         (0.004)         (0.004)   \nuniversity         -0.003          -0.000           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.025***       -0.008           0.001   \n                  (0.007)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.050           0.003           0.065   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.001           0.014***        0.002   \n                  (0.005)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.003           0.002           0.003          -0.001   \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nc.neg#c.ri~2        0.005*          0.004*          0.001           0.001   \n                  (0.002)         (0.002)         (0.002)         (0.000)   \norder              -0.001**        -0.001***       -0.000          -0.000***\n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.004           0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.011*         -0.003          -0.002           0.004*  \n                  (0.005)         (0.003)         (0.005)         (0.001)   \nuniversity          0.005           0.003          -0.002           0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.055**         0.010          -0.004           0.001   \n                  (0.019)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.007           0.012           0.009           0.002   \nr2_b                0.052           0.105           0.007           0.049   \nr2_o                0.006           0.011           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.004           0.011**         0.006***\n                  (0.003)         (0.003)         (0.001)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003           0.003*          0.001   \n                  (0.002)         (0.002)         (0.001)   \nc.neg#c.ri~2        0.002           0.003*          0.000   \n                  (0.001)         (0.001)         (0.001)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.003*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000*          0.000           0.000** \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.006          -0.000           0.000   \n                  (0.005)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.001   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.006          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.045           0.213           0.163   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.  \n.   \n. * Table A8 Row 3 \n.  \n.   replace right2= wp_right2  \n(1,265,458 real changes made)\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 & wp_right2_ext==1, re\n>   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 & political_interest_d\n> ichox==1, re  \n.   estimates store C\n.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r\n> 2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.005***        0.005***        0.003** \n                  (0.001)         (0.001)         (0.001)   \ntimesecSto~g       -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nc.neg#c.ti~g       -0.001***       -0.002***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.001           0.001           0.002   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ri~2        0.001           0.002*          0.002** \n                  (0.001)         (0.001)         (0.001)   \norder              -0.000***       -0.000***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.008***       -0.009***\n                  (0.000)         (0.000)         (0.000)   \nfemale             -0.001*         -0.000          -0.001   \n                  (0.000)         (0.000)         (0.000)   \nage                 0.000**         0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.000           0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nuniversity         -0.000           0.000          -0.001*  \n                  (0.000)         (0.000)         (0.001)   \n_cons               0.001          -0.001           0.003*  \n                  (0.001)         (0.001)         (0.002)   \n------------------------------------------------------------\nr2_w                0.005           0.005           0.005   \nr2_b                0.211           0.225           0.242   \nr2_o                0.003           0.003           0.004   \nN              666526.000      360355.000      317613.000   \nN_g               933.000         505.000         444.000   \n------------------------------------------------------------\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 , r\n> e  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 , r\n> e  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.003           0.007           0.010** \n                  (0.001)         (0.004)         (0.004)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.000          -0.002*  \n                  (0.000)         (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.001          -0.013*         -0.009          -0.008*  \n                  (0.001)         (0.005)         (0.006)         (0.004)   \nc.neg#c.ri~2        0.001           0.008           0.011*         -0.001   \n                  (0.001)         (0.005)         (0.005)         (0.003)   \norder              -0.000***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.009***       -0.008***       -0.017***\n                  (0.000)         (0.001)         (0.001)         (0.001)   \nfemale             -0.001*         -0.001           0.000          -0.002   \n                  (0.000)         (0.002)         (0.002)         (0.002)   \nage                 0.000**         0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome              0.000           0.002           0.003           0.005   \n                  (0.001)         (0.005)         (0.004)         (0.004)   \nuniversity         -0.000           0.003          -0.003          -0.002   \n                  (0.000)         (0.002)         (0.003)         (0.002)   \n_cons               0.001           0.007          -0.010           0.009   \n                  (0.001)         (0.007)         (0.008)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.006           0.012   \nr2_b                0.211           0.097           0.002           0.056   \nr2_o                0.003           0.004           0.005           0.009   \nN              666526.000       24315.000       23296.000       19125.000   \nN_g               933.000          35.000          32.000          27.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.006           0.005*  \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g        0.002          -0.000          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003***       -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005           0.003   \n                  (0.005)         (0.006)         (0.003)   \nc.neg#c.ri~2       -0.001          -0.000           0.001   \n                  (0.004)         (0.005)         (0.002)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.007***       -0.009***       -0.004***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.000           0.002          -0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.000           0.005          -0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity          0.006***       -0.005*          0.001   \n                  (0.002)         (0.003)         (0.001)   \n_cons              -0.014*          0.002          -0.003   \n                  (0.006)         (0.007)         (0.003)   \n------------------------------------------------------------\nr2_w                0.006           0.004           0.002   \nr2_b                0.015           0.014           0.015   \nr2_o                0.004           0.004           0.002   \nN               26102.000       40263.000       24849.000   \nN_g                36.000          56.000          35.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 , r\n> e \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 , r\n> e  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.001          -0.002   \n                  (0.004)         (0.002)         (0.003)   \ntimesecSto~g       -0.003**        -0.002**         0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.005          -0.005          -0.007*  \n                  (0.006)         (0.003)         (0.003)   \nc.neg#c.ri~2        0.004           0.001           0.002   \n                  (0.005)         (0.002)         (0.002)   \norder              -0.001***       -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.013***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.003          -0.003***       -0.003*  \n                  (0.002)         (0.001)         (0.001)   \nage                -0.000           0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.002           0.004*          0.000   \n                  (0.005)         (0.002)         (0.003)   \nuniversity         -0.001          -0.002          -0.003   \n                  (0.002)         (0.001)         (0.002)   \n_cons               0.019**         0.009**         0.003   \n                  (0.007)         (0.003)         (0.004)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.004   \nr2_b                0.005           0.180           0.083   \nr2_o                0.007           0.006           0.003   \nN               36766.000       42808.000       36042.000   \nN_g                51.000          60.000          50.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.002           0.005           0.005   \n                  (0.003)         (0.004)         (0.003)   \ntimesecSto~g       -0.001           0.003***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.000          -0.002*         -0.001*  \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001          -0.003          -0.003   \n                  (0.004)         (0.005)         (0.004)   \nc.neg#c.ri~2        0.003           0.006          -0.000   \n                  (0.003)         (0.004)         (0.004)   \norder              -0.001***       -0.000          -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.004***       -0.003***       -0.016***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.002           0.002          -0.004** \n                  (0.001)         (0.002)         (0.001)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.007*         -0.000          -0.000   \n                  (0.003)         (0.005)         (0.004)   \nuniversity         -0.003          -0.000           0.002   \n                  (0.002)         (0.003)         (0.002)   \n_cons               0.023**        -0.005           0.003   \n                  (0.008)         (0.011)         (0.006)   \n------------------------------------------------------------\nr2_w                0.003           0.002           0.010   \nr2_b                0.088           0.001           0.058   \nr2_o                0.002           0.002           0.008   \nN               51367.000       22728.000       26122.000   \nN_g                71.000          32.000          37.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 , re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 , re \n>  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 , re \n>  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 , re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 , re \n>  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 , re \n>  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 , re \n>  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.003           0.013**         0.001   \n                  (0.006)         (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.004**        -0.001          -0.000          -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** \n                  (0.001)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.003           0.010           0.008          -0.001   \n                  (0.009)         (0.005)         (0.004)         (0.001)   \nc.neg#c.ri~2        0.005           0.003           0.001           0.001   \n                  (0.007)         (0.004)         (0.004)         (0.001)   \norder              -0.001**        -0.001***       -0.000          -0.000** \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.021***       -0.014***       -0.003***\n                  (0.001)         (0.001)         (0.001)         (0.001)   \nfemale             -0.002          -0.003           0.002          -0.001** \n                  (0.003)         (0.002)         (0.002)         (0.000)   \nage                -0.001          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome             -0.010          -0.001          -0.002           0.004*  \n                  (0.005)         (0.004)         (0.005)         (0.001)   \nuniversity          0.005           0.002          -0.002          -0.000   \n                  (0.004)         (0.002)         (0.003)         (0.000)   \n_cons               0.045*          0.009          -0.007           0.001   \n                  (0.021)         (0.006)         (0.007)         (0.002)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.012           0.009           0.002   \nr2_b                0.091           0.072           0.000           0.045   \nr2_o                0.006           0.010           0.008           0.002   \nN               25380.000       23150.000       22867.000       33376.000   \nN_g                36.000          32.000          32.000          48.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.003           0.010**         0.006***\n                  (0.003)         (0.003)         (0.002)   \ntimesecSto~g       -0.001          -0.001           0.001***\n                  (0.001)         (0.001)         (0.000)   \nc.neg#c.ti~g        0.000          -0.003***       -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.001           0.001           0.001   \n                  (0.004)         (0.004)         (0.002)   \nc.neg#c.ri~2       -0.001           0.006          -0.000   \n                  (0.003)         (0.004)         (0.002)   \norder              -0.000          -0.001**        -0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.012***       -0.006***\n                  (0.001)         (0.001)         (0.000)   \nfemale              0.003          -0.004*          0.000   \n                  (0.002)         (0.002)         (0.001)   \nage                 0.000           0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.008           0.000           0.000   \n                  (0.004)         (0.003)         (0.001)   \nuniversity          0.002           0.002           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.001           0.008          -0.008***\n                  (0.005)         (0.005)         (0.002)   \n------------------------------------------------------------\nr2_w                0.006           0.008           0.004   \nr2_b                0.008           0.348           0.181   \nr2_o                0.006           0.005           0.002   \nN               22094.000       35294.000      130582.000   \nN_g                31.000          48.000         184.000   \n------------------------------------------------------------\n.     \n.         \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 & wp_right2_ext==1, re\n>   \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 & wp_\n> right2_ext==1, re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 & w\n> p_right2_ext==1, re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 & w\n> p_right2_ext==1, re  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 & wp_\n> right2_ext==1, re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store F \n.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005***        0.008           0.015*          0.009*  \n                  (0.001)         (0.005)         (0.007)         (0.004)   \ntimesecSto~g       -0.000          -0.003*          0.002          -0.001   \n                  (0.000)         (0.001)         (0.002)         (0.001)   \nc.neg#c.ti~g       -0.002***       -0.003*         -0.004*         -0.003** \n                  (0.000)         (0.001)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.001          -0.014**        -0.005          -0.007   \n                  (0.001)         (0.005)         (0.008)         (0.004)   \nc.neg#c.ri~2        0.002*          0.008           0.009          -0.001   \n                  (0.001)         (0.005)         (0.006)         (0.003)   \norder              -0.000***       -0.000          -0.002***       -0.001*  \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.008***       -0.006***       -0.009***       -0.014***\n                  (0.000)         (0.001)         (0.001)         (0.002)   \nfemale             -0.000          -0.003           0.004          -0.000   \n                  (0.000)         (0.003)         (0.004)         (0.003)   \nage                 0.000*         -0.000           0.002**         0.000   \n                  (0.000)         (0.000)         (0.001)         (0.000)   \nincome              0.001           0.009           0.000           0.008   \n                  (0.001)         (0.008)         (0.007)         (0.005)   \nuniversity          0.000           0.003          -0.006          -0.002   \n                  (0.000)         (0.003)         (0.006)         (0.002)   \n_cons              -0.001           0.019*         -0.037*          0.006   \n                  (0.001)         (0.010)         (0.017)         (0.007)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.003           0.008           0.010   \nr2_b                0.225           0.423           0.018           0.197   \nr2_o                0.003           0.003           0.006           0.007   \nN              360355.000       12097.000       11669.000       11212.000   \nN_g               505.000          17.000          16.000          16.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010**         0.010*         -0.003   \n                  (0.004)         (0.004)         (0.003)   \ntimesecSto~g        0.001          -0.001          -0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.003**        -0.003**         0.000   \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.016***       -0.007           0.003   \n                  (0.005)         (0.007)         (0.004)   \nc.neg#c.ri~2       -0.003           0.000           0.003   \n                  (0.003)         (0.005)         (0.002)   \norder              -0.001*         -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.006***       -0.010***       -0.010***\n                  (0.001)         (0.001)         (0.001)   \nfemale              0.001           0.004          -0.000   \n                  (0.002)         (0.002)         (0.002)   \nage                 0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.014*          0.005          -0.004   \n                  (0.006)         (0.005)         (0.004)   \nuniversity          0.010***       -0.004           0.002   \n                  (0.002)         (0.004)         (0.002)   \n_cons              -0.027***        0.002          -0.002   \n                  (0.007)         (0.008)         (0.005)   \n------------------------------------------------------------\nr2_w                0.006           0.005           0.005   \nr2_b                0.126           0.010           0.032   \nr2_o                0.005           0.005           0.005   \nN               13657.000       30367.000       12762.000   \nN_g                19.000          42.000          18.000   \n------------------------------------------------------------\n.     \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 & wp_\n> right2_ext==1, re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 & w\n> p_right2_ext==1, re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 & w\n> p_right2_ext==1, re  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.018**         0.001           0.001   \n                  (0.006)         (0.003)         (0.004)   \ntimesecSto~g       -0.004*         -0.002*          0.001   \n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.005**        -0.000          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.016          -0.006*         -0.012** \n                  (0.009)         (0.003)         (0.004)   \nc.neg#c.ri~2        0.005           0.001           0.001   \n                  (0.005)         (0.002)         (0.003)   \norder              -0.001*         -0.001***       -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.013***       -0.009***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.007*         -0.002          -0.001   \n                  (0.003)         (0.001)         (0.002)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.017*          0.004*         -0.011*  \n                  (0.008)         (0.002)         (0.005)   \nuniversity         -0.001           0.001          -0.000   \n                  (0.003)         (0.001)         (0.002)   \n_cons               0.015           0.009*          0.010   \n                  (0.010)         (0.004)         (0.007)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.006   \nr2_b                0.019           0.012           0.096   \nr2_o                0.008           0.006           0.004   \nN               16651.000       23760.000       19926.000   \nN_g                23.000          33.000          28.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.001           0.002           0.002   \n                  (0.003)         (0.006)         (0.004)   \ntimesecSto~g        0.001           0.005***        0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.000          -0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.004          -0.002          -0.001   \n                  (0.005)         (0.006)         (0.005)   \nc.neg#c.ri~2        0.004           0.006           0.001   \n                  (0.003)         (0.005)         (0.004)   \norder              -0.000*         -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.002***       -0.003*         -0.020***\n                  (0.001)         (0.001)         (0.002)   \nfemale              0.001           0.001          -0.007***\n                  (0.002)         (0.003)         (0.002)   \nage                -0.000          -0.000          -0.001   \n                  (0.000)         (0.002)         (0.000)   \nincome             -0.003           0.001           0.010   \n                  (0.005)         (0.010)         (0.005)   \nuniversity          0.001           0.001           0.011*  \n                  (0.003)         (0.007)         (0.005)   \n_cons               0.001          -0.017          -0.000   \n                  (0.011)         (0.034)         (0.014)   \n------------------------------------------------------------\nr2_w                0.001           0.003           0.012   \nr2_b                0.001           0.023           0.007   \nr2_o                0.001           0.002           0.011   \nN               29739.000       11375.000       13141.000   \nN_g                42.000          16.000          19.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 & wp_\n> right2_ext==1, re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 & wp_\n> right2_ext==1, re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 & wp_\n> right2_ext==1, re  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.005           0.010           0.003   \n                  (0.009)         (0.004)         (0.006)         (0.002)   \ntimesecSto~g       -0.005*         -0.001           0.003          -0.001*  \n                  (0.002)         (0.001)         (0.002)         (0.000)   \nc.neg#c.ti~g       -0.001          -0.001          -0.002          -0.001** \n                  (0.002)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2             -0.001           0.010           0.006          -0.002   \n                  (0.012)         (0.006)         (0.006)         (0.002)   \nc.neg#c.ri~2        0.005           0.002           0.001           0.002   \n                  (0.008)         (0.004)         (0.005)         (0.001)   \norder              -0.001          -0.000          -0.001          -0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.019***       -0.020***       -0.016***       -0.004***\n                  (0.002)         (0.002)         (0.002)         (0.001)   \nfemale              0.002          -0.000           0.003          -0.001   \n                  (0.005)         (0.003)         (0.003)         (0.001)   \nage                -0.003          -0.000           0.000           0.000   \n                  (0.002)         (0.000)         (0.000)         (0.000)   \nincome             -0.008          -0.005           0.001           0.003   \n                  (0.008)         (0.005)         (0.007)         (0.002)   \nuniversity          0.017           0.007*         -0.022*         -0.000   \n                  (0.011)         (0.003)         (0.009)         (0.001)   \n_cons               0.071*          0.006           0.000           0.004   \n                  (0.035)         (0.007)             (.)         (0.003)   \n----------------------------------------------------------------------------\nr2_w                0.009           0.012           0.011           0.002   \nr2_b                0.035           0.009           0.044           0.084   \nr2_o                0.009           0.010           0.010           0.002   \nN               12381.000       13628.000       12261.000       17370.000   \nN_g                17.000          19.000          17.000          25.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.000          -0.002           0.006** \n                  (0.003)         (0.003)         (0.002)   \ntimesecSto~g       -0.002**        -0.001           0.000   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.000          -0.000          -0.002***\n                  (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.003          -0.007           0.001   \n                  (0.003)         (0.004)         (0.002)   \nc.neg#c.ri~2       -0.001           0.007*         -0.001   \n                  (0.002)         (0.003)         (0.002)   \norder              -0.000          -0.000*         -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015***       -0.011***       -0.007***\n                  (0.002)         (0.001)         (0.001)   \nfemale              0.001          -0.004*          0.001   \n                  (0.003)         (0.002)         (0.001)   \nage                -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.012*          0.012**         0.001   \n                  (0.005)         (0.004)         (0.002)   \nuniversity         -0.000           0.003           0.000   \n                  (0.002)         (0.002)         (0.001)   \n_cons               0.017*          0.001          -0.003   \n                  (0.007)         (0.005)         (0.003)   \n------------------------------------------------------------\nr2_w                0.009           0.008           0.004   \nr2_b                0.010           0.081           0.229   \nr2_o                0.008           0.006           0.003   \nN               10559.000       17812.000       69988.000   \nN_g                15.000          24.000          99.000   \n------------------------------------------------------------\n.  \n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 0 to 1629\n                delta:  1 unit\n.   replace neg = negativity\n(0 real changes made)\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & local==0 & political_interest_d\n> ichox==1, re  \n.   estimates store G  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.e\" & period==2 & local==0 & p\n> olitical_interest_dichox==1, re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & local==0 & p\n> olitical_interest_dichox==1, re  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store F \n.   esttab G A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b\n>  r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003**         0.002          -0.004           0.010** \n                  (0.001)         (0.007)         (0.008)         (0.003)   \ntimesecSto~g       -0.000          -0.002           0.003          -0.002*  \n                  (0.000)         (0.002)         (0.002)         (0.001)   \nc.neg#c.ti~g       -0.001***       -0.001           0.001          -0.003***\n                  (0.000)         (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.002          -0.013           0.028          -0.008   \n                  (0.001)         (0.009)         (0.028)         (0.004)   \nc.neg#c.ri~2        0.002**         0.009          -0.023          -0.001   \n                  (0.001)         (0.007)         (0.024)         (0.004)   \norder              -0.001***       -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.009***       -0.009***       -0.007***       -0.017***\n                  (0.000)         (0.001)         (0.002)         (0.001)   \nfemale             -0.001           0.002          -0.004          -0.004   \n                  (0.000)         (0.004)         (0.005)         (0.002)   \nage                 0.000           0.000           0.001           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nincome             -0.001           0.006           0.002           0.003   \n                  (0.001)         (0.008)         (0.009)         (0.004)   \nuniversity         -0.001*          0.004           0.009          -0.002   \n                  (0.001)         (0.004)         (0.010)         (0.002)   \n_cons               0.003*          0.007          -0.029           0.010   \n                  (0.002)         (0.012)         (0.021)         (0.006)   \n----------------------------------------------------------------------------\nr2_w                0.005           0.004           0.004           0.012   \nr2_b                0.242           0.048           0.137           0.033   \nr2_o                0.004           0.004           0.004           0.009   \nN              317613.000       13363.000        8104.000       17783.000   \nN_g               444.000          19.000          11.000          25.000   \n----------------------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.018**         0.002           0.006*  \n                  (0.007)         (0.004)         (0.003)   \ntimesecSto~g        0.001          -0.000          -0.002*  \n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.005**        -0.001          -0.001*  \n                  (0.002)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.003           0.010           0.009*  \n                  (0.009)         (0.007)         (0.004)   \nc.neg#c.ri~2        0.003           0.001           0.002   \n                  (0.007)         (0.006)         (0.003)   \norder              -0.001**        -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.010***       -0.010***       -0.007***\n                  (0.001)         (0.001)         (0.001)   \nfemale             -0.008          -0.003           0.003   \n                  (0.004)         (0.002)         (0.002)   \nage                 0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.041**         0.002          -0.001   \n                  (0.015)         (0.005)         (0.003)   \nuniversity          0.007          -0.008**         0.003*  \n                  (0.005)         (0.003)         (0.002)   \n_cons               0.006           0.009          -0.002   \n                  (0.012)         (0.008)         (0.004)   \n------------------------------------------------------------\nr2_w                0.006           0.005           0.005   \nr2_b                0.010           0.021           0.167   \nr2_o                0.005           0.004           0.005   \nN               10828.000       28830.000       11162.000   \nN_g                15.000          40.000          16.000   \n------------------------------------------------------------\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & local==0 & p\n> olitical_interest_dichox==1, re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & local==0 & p\n> olitical_interest_dichox==1, re  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store F \n.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.002          -0.003           0.001   \n                  (0.006)         (0.003)         (0.005)   \ntimesecSto~g       -0.006***       -0.001           0.001   \n                  (0.002)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.001           0.001          -0.001   \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.027*         -0.005          -0.007   \n                  (0.011)         (0.003)         (0.004)   \nc.neg#c.ri~2        0.005          -0.001           0.006   \n                  (0.007)         (0.003)         (0.004)   \norder              -0.001*         -0.000**        -0.001***\n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.013***       -0.009***       -0.010***\n                  (0.002)         (0.001)         (0.001)   \nfemale             -0.002          -0.002           0.000   \n                  (0.003)         (0.001)         (0.003)   \nage                 0.000           0.000**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.005           0.008***        0.004   \n                  (0.007)         (0.002)         (0.005)   \nuniversity          0.000          -0.001          -0.004   \n                  (0.003)         (0.001)         (0.002)   \n_cons               0.033**        -0.003           0.008   \n                  (0.010)         (0.005)         (0.007)   \n------------------------------------------------------------\nr2_w                0.008           0.005           0.006   \nr2_b                0.060           0.063           0.187   \nr2_o                0.007           0.005           0.004   \nN               12957.000       19843.000       19051.000   \nN_g                18.000          28.000          26.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                -0.006          -0.001           0.012** \n                  (0.004)         (0.006)         (0.004)   \ntimesecSto~g       -0.001           0.003*          0.001   \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g        0.001          -0.002          -0.003** \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.004           0.010           0.008   \n                  (0.006)         (0.009)         (0.008)   \nc.neg#c.ri~2        0.008           0.017*         -0.002   \n                  (0.005)         (0.008)         (0.006)   \norder              -0.001***       -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.006***       -0.003**        -0.014***\n                  (0.001)         (0.001)         (0.002)   \nfemale             -0.001           0.003          -0.002   \n                  (0.002)         (0.003)         (0.002)   \nage                -0.001          -0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.012**        -0.001           0.001   \n                  (0.004)         (0.007)         (0.007)   \nuniversity         -0.005*         -0.004          -0.001   \n                  (0.003)         (0.006)         (0.004)   \n_cons               0.031**        -0.005           0.001   \n                  (0.010)         (0.015)         (0.009)   \n------------------------------------------------------------\nr2_w                0.005           0.002           0.008   \nr2_b                0.115           0.043           0.017   \nr2_o                0.002           0.002           0.008   \nN               33832.000       13226.000        9546.000   \nN_g                47.000          19.000          13.000   \n------------------------------------------------------------\n.  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & local==0 & pol\n> itical_interest_dichox==1, re  \n.   estimates store G \n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.002          -0.004           0.019**         0.001   \n                  (0.009)         (0.005)         (0.007)         (0.002)   \ntimesecSto~g       -0.007**        -0.001           0.002          -0.001***\n                  (0.002)         (0.001)         (0.002)         (0.000)   \nc.neg#c.ti~g       -0.000           0.001          -0.004**        -0.001   \n                  (0.002)         (0.001)         (0.001)         (0.000)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.002           0.008           0.017**        -0.001   \n                  (0.014)         (0.006)         (0.006)         (0.002)   \nc.neg#c.ri~2        0.003           0.003          -0.003           0.002   \n                  (0.010)         (0.005)         (0.005)         (0.002)   \norder              -0.001          -0.001***        0.000          -0.000** \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.012***       -0.026***       -0.015***       -0.003***\n                  (0.002)         (0.002)         (0.002)         (0.001)   \nfemale              0.001          -0.008**         0.003          -0.001   \n                  (0.006)         (0.003)         (0.003)         (0.001)   \nage                -0.002          -0.000           0.000           0.000*  \n                  (0.001)         (0.000)         (0.000)         (0.000)   \nincome              0.001          -0.002          -0.000           0.009***\n                  (0.010)         (0.005)         (0.007)         (0.003)   \nuniversity          0.070          -0.001          -0.007           0.001   \n                  (0.039)         (0.003)         (0.006)         (0.001)   \n_cons               0.000           0.019*         -0.024*         -0.000   \n                      (.)         (0.008)         (0.012)         (0.003)   \n----------------------------------------------------------------------------\nr2_w                0.006           0.015           0.010           0.003   \nr2_b                0.057           0.000           0.212           0.120   \nr2_o                0.005           0.014           0.010           0.003   \nN               12112.000       14469.000       11497.000       18203.000   \nN_g                17.000          20.000          16.000          27.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.001           0.005           0.008** \n                  (0.004)         (0.005)         (0.003)   \ntimesecSto~g       -0.002*         -0.003           0.002*  \n                  (0.001)         (0.001)         (0.001)   \nc.neg#c.ti~g       -0.000          -0.002          -0.002** \n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.000          -0.011          -0.001   \n                  (0.005)         (0.009)         (0.003)   \nc.neg#c.ri~2       -0.000           0.001           0.000   \n                  (0.004)         (0.006)         (0.003)   \norder              -0.000          -0.001**        -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.019***       -0.028***       -0.011***\n                  (0.002)         (0.002)         (0.001)   \nfemale              0.005           0.001           0.001   \n                  (0.003)         (0.003)         (0.001)   \nage                 0.000*          0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.016*          0.009          -0.004   \n                  (0.007)         (0.008)         (0.003)   \nuniversity         -0.001          -0.003           0.003*  \n                  (0.003)         (0.004)         (0.002)   \n_cons               0.012           0.015          -0.008   \n                  (0.007)         (0.010)         (0.004)   \n------------------------------------------------------------\nr2_w                0.010           0.016           0.007   \nr2_b                0.069           0.311           0.114   \nr2_o                0.010           0.014           0.006   \nN                7754.000       11734.000       43319.000   \nN_g                11.000          16.000          60.000   \n------------------------------------------------------------\n.  \n.   \n.   \n.   \n.       \n"} -->
<pre><code>. *** Syntax for analyses of time-series video data
. *** Use data file 'Time-series-data-videos.dta' with this syntax
. * Table 4
.   gen neg = .
(1,327,271 missing values generated)
.   replace neg = negativity
(914,368 real changes made)
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc
&gt; ome university if period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc
&gt; ome university if wp_right2_dichox==0 &amp; period==2 &amp; local==0 , re 
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc
&gt; ome university if wp_right2_dichox==1 &amp; period==2 &amp; local==0 , re 
.   estimates store C
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.wp_right2 order L.g
&gt; slmc female age income university if period==2 &amp; local==0 , re 
.   estimates store D
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.006***        0.005***        0.005***
                  (0.001)         (0.001)         (0.001)         (0.001)   
timesecSto~g       -0.000           0.000          -0.001*         -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
c.neg#c.ti~g       -0.001***       -0.002***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)         (0.000)   
order              -0.000***       -0.000***       -0.000***       -0.000***
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.008***       -0.008***       -0.008***
                  (0.000)         (0.000)         (0.000)         (0.000)   
female             -0.001*         -0.001*         -0.000          -0.001*  
                  (0.000)         (0.000)         (0.000)         (0.000)   
age                 0.000**         0.000*          0.000*          0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000          -0.000           0.001           0.000   
                  (0.001)         (0.001)         (0.001)         (0.001)   
university         -0.000          -0.001          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)         (0.000)   
neg                                                                 0.000   
                                                                      (.)   
wp_right2                                                           0.001   
                                                                  (0.001)   
c.neg#c.wp~2                                                        0.001   
                                                                  (0.001)   
_cons               0.001          -0.000           0.002           0.001   
                  (0.001)         (0.001)         (0.001)         (0.001)   
----------------------------------------------------------------------------
r2_w                0.005           0.005           0.005           0.005   
r2_b                0.214           0.218           0.206           0.211   
r2_o                0.003           0.003           0.003           0.003   
N              666526.000      335833.000      330693.000      666526.000   
N_g               933.000         471.000         462.000         933.000   
----------------------------------------------------------------------------
.   
.   
. * Figure 4
.   
.   gen right2 = .
(1,327,271 missing values generated)
.   replace right2= wp_right2
(1,316,553 real changes made)
.    
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.003           0.007           0.010** 
                  (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.002           0.000          -0.002*  
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001          -0.002*         -0.003***
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.013*         -0.009          -0.008*  
                  (0.005)         (0.006)         (0.004)   
c.neg#c.ri~2        0.008           0.011*         -0.001   
                  (0.005)         (0.005)         (0.003)   
order              -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.009***       -0.008***       -0.017***
                  (0.001)         (0.001)         (0.001)   
female             -0.001           0.000          -0.002   
                  (0.002)         (0.002)         (0.002)   
age                 0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.003           0.005   
                  (0.005)         (0.004)         (0.004)   
university          0.003          -0.003          -0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.007          -0.010           0.009   
                  (0.007)         (0.008)         (0.006)   
------------------------------------------------------------
r2_w                0.004           0.006           0.012   
r2_b                0.097           0.002           0.056   
r2_o                0.004           0.005           0.009   
N               24315.000       23296.000       19125.000   
N_g                35.000          32.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.005*  
                  (0.004)         (0.004)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005           0.003   
                  (0.005)         (0.006)         (0.003)   
c.neg#c.ri~2       -0.001          -0.000           0.001   
                  (0.004)         (0.005)         (0.002)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female             -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.000           0.005          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006***       -0.005*          0.001   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.014*          0.002          -0.003   
                  (0.006)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.015           0.014           0.015   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.001          -0.002   
                  (0.004)         (0.002)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005          -0.007*  
                  (0.006)         (0.003)         (0.003)   
c.neg#c.ri~2        0.004           0.001           0.002   
                  (0.005)         (0.002)         (0.002)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.003***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.004*          0.000   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.003   
                  (0.002)         (0.001)         (0.002)   
_cons               0.019**         0.009**         0.003   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.008           0.004   
r2_b                0.005           0.180           0.083   
r2_o                0.007           0.006           0.003   
N               36766.000       42808.000       36042.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.005           0.005   
                  (0.003)         (0.004)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001          -0.003          -0.003   
                  (0.004)         (0.005)         (0.004)   
c.neg#c.ri~2        0.003           0.006          -0.000   
                  (0.003)         (0.004)         (0.004)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*         -0.000          -0.000   
                  (0.003)         (0.005)         (0.004)   
university         -0.003          -0.000           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.023**        -0.005           0.003   
                  (0.008)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.088           0.001           0.058   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.003           0.013**         0.001   
                  (0.006)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.003           0.010           0.008          -0.001   
                  (0.009)         (0.005)         (0.004)         (0.001)   
c.neg#c.ri~2        0.005           0.003           0.001           0.001   
                  (0.007)         (0.004)         (0.004)         (0.001)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.003           0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.010          -0.001          -0.002           0.004*  
                  (0.005)         (0.004)         (0.005)         (0.001)   
university          0.005           0.002          -0.002          -0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.045*          0.009          -0.007           0.001   
                  (0.021)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.091           0.072           0.000           0.045   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.010**         0.006***
                  (0.003)         (0.003)         (0.002)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001           0.001           0.001   
                  (0.004)         (0.004)         (0.002)   
c.neg#c.ri~2       -0.001           0.006          -0.000   
                  (0.003)         (0.004)         (0.002)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income             -0.008           0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.008          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.008           0.348           0.181   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.  
. * Table A3 Row 3
.   replace right2= wp_right2
(0 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.003           0.007           0.010** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.001          -0.013*         -0.009          -0.008*  
                  (0.001)         (0.005)         (0.006)         (0.004)   
c.neg#c.ri~2        0.001           0.008           0.011*         -0.001   
                  (0.001)         (0.005)         (0.005)         (0.003)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001           0.000          -0.002   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**         0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.002           0.003           0.005   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.003          -0.003          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.007          -0.010           0.009   
                  (0.001)         (0.007)         (0.008)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.211           0.097           0.002           0.056   
r2_o                0.003           0.004           0.005           0.009   
N              666526.000       24315.000       23296.000       19125.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.005*  
                  (0.004)         (0.004)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005           0.003   
                  (0.005)         (0.006)         (0.003)   
c.neg#c.ri~2       -0.001          -0.000           0.001   
                  (0.004)         (0.005)         (0.002)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female             -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.000           0.005          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006***       -0.005*          0.001   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.014*          0.002          -0.003   
                  (0.006)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.015           0.014           0.015   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.001          -0.002   
                  (0.004)         (0.002)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005          -0.007*  
                  (0.006)         (0.003)         (0.003)   
c.neg#c.ri~2        0.004           0.001           0.002   
                  (0.005)         (0.002)         (0.002)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.003***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.004*          0.000   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.003   
                  (0.002)         (0.001)         (0.002)   
_cons               0.019**         0.009**         0.003   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.008           0.004   
r2_b                0.005           0.180           0.083   
r2_o                0.007           0.006           0.003   
N               36766.000       42808.000       36042.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.005           0.005   
                  (0.003)         (0.004)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001          -0.003          -0.003   
                  (0.004)         (0.005)         (0.004)   
c.neg#c.ri~2        0.003           0.006          -0.000   
                  (0.003)         (0.004)         (0.004)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*         -0.000          -0.000   
                  (0.003)         (0.005)         (0.004)   
university         -0.003          -0.000           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.023**        -0.005           0.003   
                  (0.008)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.088           0.001           0.058   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.003           0.013**         0.001   
                  (0.006)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.003           0.010           0.008          -0.001   
                  (0.009)         (0.005)         (0.004)         (0.001)   
c.neg#c.ri~2        0.005           0.003           0.001           0.001   
                  (0.007)         (0.004)         (0.004)         (0.001)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.003           0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.010          -0.001          -0.002           0.004*  
                  (0.005)         (0.004)         (0.005)         (0.001)   
university          0.005           0.002          -0.002          -0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.045*          0.009          -0.007           0.001   
                  (0.021)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.091           0.072           0.000           0.045   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.010**         0.006***
                  (0.003)         (0.003)         (0.002)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001           0.001           0.001   
                  (0.004)         (0.004)         (0.002)   
c.neg#c.ri~2       -0.001           0.006          -0.000   
                  (0.003)         (0.004)         (0.002)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income             -0.008           0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.008          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.008           0.348           0.181   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==1 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==1 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==1 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==1 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==1 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.001           0.017*         -0.015           0.003   
                  (0.001)         (0.007)         (0.011)         (0.010)   
timesecSto~g       -0.001*          0.000          -0.003          -0.004   
                  (0.000)         (0.002)         (0.002)         (0.002)   
c.neg#c.ti~g       -0.000          -0.004**         0.004          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.003)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.001          -0.031**        -0.004          -0.017*  
                  (0.001)         (0.010)         (0.011)         (0.008)   
c.neg#c.ri~2       -0.001          -0.001           0.011           0.009   
                  (0.001)         (0.007)         (0.009)         (0.007)   
order              -0.000***       -0.001          -0.001          -0.000   
                  (0.000)         (0.000)         (0.001)         (0.000)   
L.gslmc            -0.008***       -0.015***       -0.006***       -0.025***
                  (0.000)         (0.002)         (0.002)         (0.003)   
female             -0.000          -0.008*          0.006          -0.008   
                  (0.001)         (0.004)         (0.005)         (0.004)   
age                 0.000*         -0.002***        0.001           0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.001           0.018*          0.004          -0.004   
                  (0.001)         (0.009)         (0.008)         (0.008)   
university         -0.001**         0.006          -0.012           0.003   
                  (0.001)         (0.004)         (0.006)         (0.004)   
_cons               0.003           0.044**         0.001           0.023*  
                  (0.002)         (0.015)         (0.017)         (0.011)   
----------------------------------------------------------------------------
r2_w                0.008           0.017           0.007           0.018   
r2_b                0.208           0.001           0.032           0.121   
r2_o                0.003           0.010           0.003           0.012   
N              232990.000        7770.000        6336.000        5346.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.007          -0.010          -0.001   
                  (0.008)         (0.006)         (0.002)   
timesecSto~g       -0.008**        -0.001          -0.001   
                  (0.003)         (0.002)         (0.001)   
c.neg#c.ti~g        0.003           0.002           0.000   
                  (0.002)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.004          -0.028*         -0.003   
                  (0.013)         (0.012)         (0.005)   
c.neg#c.ri~2       -0.006           0.002           0.001   
                  (0.009)         (0.007)         (0.002)   
order              -0.000          -0.001          -0.000   
                  (0.001)         (0.000)         (0.000)   
L.gslmc            -0.009***       -0.007***       -0.014***
                  (0.003)         (0.001)         (0.002)   
female              0.004           0.002          -0.000   
                  (0.004)         (0.003)         (0.002)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.001           0.000           0.003   
                  (0.012)         (0.007)         (0.003)   
university          0.004           0.007           0.000   
                  (0.004)         (0.004)         (0.002)   
_cons               0.013           0.003          -0.001   
                  (0.014)         (0.012)         (0.005)   
------------------------------------------------------------
r2_w                0.011           0.010           0.012   
r2_b                0.225           0.074           0.106   
r2_o                0.004           0.003           0.007   
N                5004.000       10920.000        8855.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==1 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==1 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==1 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.028***        0.017***       -0.000   
                  (0.007)         (0.003)         (0.005)   
timesecSto~g       -0.005*         -0.004***        0.000   
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ti~g        0.008***       -0.004***       -0.000   
                  (0.002)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.034**        -0.006           0.000   
                  (0.012)         (0.006)         (0.004)   
c.neg#c.ri~2       -0.009          -0.004           0.001   
                  (0.010)         (0.003)         (0.003)   
order              -0.001          -0.000*         -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.022***       -0.010***       -0.001   
                  (0.002)         (0.001)         (0.001)   
female             -0.010**        -0.001          -0.001   
                  (0.004)         (0.002)         (0.002)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.004          -0.002           0.002   
                  (0.009)         (0.003)         (0.003)   
university          0.004          -0.000          -0.002   
                  (0.004)         (0.002)         (0.002)   
_cons               0.044***        0.015*         -0.005   
                  (0.013)         (0.006)         (0.006)   
------------------------------------------------------------
r2_w                0.016           0.015           0.001   
r2_b                0.026           0.562           0.009   
r2_o                0.012           0.007           0.000   
N               14076.000       14940.000       14500.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.000           0.034***        0.012   
                  (0.006)         (0.009)         (0.011)   
timesecSto~g       -0.003          -0.004*          0.002   
                  (0.001)         (0.002)         (0.004)   
c.neg#c.ti~g       -0.000          -0.010***       -0.003   
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.003          -0.002           0.023   
                  (0.007)         (0.008)         (0.016)   
c.neg#c.ri~2        0.007           0.006          -0.028*  
                  (0.006)         (0.008)         (0.014)   
order              -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.005***       -0.010***       -0.021***
                  (0.001)         (0.002)         (0.003)   
female              0.000           0.003           0.003   
                  (0.002)         (0.003)         (0.003)   
age                -0.000          -0.001          -0.001*  
                  (0.000)         (0.001)         (0.000)   
income              0.003          -0.013          -0.025** 
                  (0.005)         (0.008)         (0.009)   
university         -0.006*         -0.000          -0.006   
                  (0.003)         (0.006)         (0.005)   
_cons               0.017           0.036           0.024   
                  (0.013)         (0.022)         (0.019)   
------------------------------------------------------------
r2_w                0.006           0.007           0.017   
r2_b                0.275           0.059           0.003   
r2_o                0.002           0.007           0.011   
N               18389.000        8288.000        6142.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==1 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==1 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==1 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.016          -0.023***        0.017*          0.002   
                  (0.008)         (0.007)         (0.007)         (0.001)   
timesecSto~g       -0.007*         -0.010***       -0.000           0.000   
                  (0.003)         (0.002)         (0.002)         (0.000)   
c.neg#c.ti~g        0.006**         0.006**        -0.003          -0.001*  
                  (0.002)         (0.002)         (0.002)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.021          -0.018           0.011          -0.003   
                  (0.018)         (0.013)         (0.006)         (0.002)   
c.neg#c.ri~2       -0.004           0.009          -0.007           0.001   
                  (0.013)         (0.007)         (0.005)         (0.001)   
order              -0.001*         -0.000          -0.000           0.000   
                  (0.001)         (0.001)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.034***       -0.007***        0.000   
                  (0.002)         (0.003)         (0.001)         (0.001)   
female              0.007          -0.009           0.003          -0.000   
                  (0.004)         (0.005)         (0.003)         (0.001)   
age                -0.002          -0.000           0.000           0.000   
                  (0.001)         (0.000)         (0.000)         (0.000)   
income              0.003           0.002          -0.012          -0.001   
                  (0.008)         (0.008)         (0.007)         (0.002)   
university          0.001          -0.007           0.002          -0.001   
                  (0.006)         (0.005)         (0.004)         (0.001)   
_cons               0.035           0.067***       -0.011          -0.003   
                  (0.033)         (0.015)         (0.010)         (0.003)   
----------------------------------------------------------------------------
r2_w                0.014           0.030           0.007           0.000   
r2_b                0.021           0.051           0.001           0.195   
r2_o                0.010           0.020           0.005           0.001   
N                8064.000        6688.000        8700.000       11616.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011          -0.000           0.009***
                  (0.006)         (0.004)         (0.002)   
timesecSto~g        0.001           0.002           0.002** 
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003          -0.000          -0.002***
                  (0.002)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.004          -0.008           0.002   
                  (0.006)         (0.006)         (0.003)   
c.neg#c.ri~2        0.000          -0.003           0.002   
                  (0.006)         (0.004)         (0.003)   
order              -0.001**        -0.000          -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.009***       -0.006***
                  (0.002)         (0.001)         (0.001)   
female              0.000          -0.001          -0.000   
                  (0.003)         (0.002)         (0.001)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.021**         0.004          -0.001   
                  (0.008)         (0.004)         (0.002)   
university         -0.002           0.002          -0.001   
                  (0.003)         (0.003)         (0.001)   
_cons              -0.006          -0.011          -0.005   
                  (0.009)         (0.007)         (0.004)   
------------------------------------------------------------
r2_w                0.010           0.005           0.006   
r2_b                0.000           0.029           0.150   
r2_o                0.007           0.004           0.003   
N                6975.000       16176.000       54205.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.   
.  
. * Table A6 Row 3
.   replace right2= wp_right2
(0 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.003           0.007           0.010** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.001          -0.013*         -0.009          -0.008*  
                  (0.001)         (0.005)         (0.006)         (0.004)   
c.neg#c.ri~2        0.001           0.008           0.011*         -0.001   
                  (0.001)         (0.005)         (0.005)         (0.003)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001           0.000          -0.002   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**         0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.002           0.003           0.005   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.003          -0.003          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.007          -0.010           0.009   
                  (0.001)         (0.007)         (0.008)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.211           0.097           0.002           0.056   
r2_o                0.003           0.004           0.005           0.009   
N              666526.000       24315.000       23296.000       19125.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.005*  
                  (0.004)         (0.004)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005           0.003   
                  (0.005)         (0.006)         (0.003)   
c.neg#c.ri~2       -0.001          -0.000           0.001   
                  (0.004)         (0.005)         (0.002)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female             -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.000           0.005          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006***       -0.005*          0.001   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.014*          0.002          -0.003   
                  (0.006)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.015           0.014           0.015   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.001          -0.002   
                  (0.004)         (0.002)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005          -0.007*  
                  (0.006)         (0.003)         (0.003)   
c.neg#c.ri~2        0.004           0.001           0.002   
                  (0.005)         (0.002)         (0.002)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.003***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.004*          0.000   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.003   
                  (0.002)         (0.001)         (0.002)   
_cons               0.019**         0.009**         0.003   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.008           0.004   
r2_b                0.005           0.180           0.083   
r2_o                0.007           0.006           0.003   
N               36766.000       42808.000       36042.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.005           0.005   
                  (0.003)         (0.004)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001          -0.003          -0.003   
                  (0.004)         (0.005)         (0.004)   
c.neg#c.ri~2        0.003           0.006          -0.000   
                  (0.003)         (0.004)         (0.004)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*         -0.000          -0.000   
                  (0.003)         (0.005)         (0.004)   
university         -0.003          -0.000           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.023**        -0.005           0.003   
                  (0.008)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.088           0.001           0.058   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.003           0.013**         0.001   
                  (0.006)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.003           0.010           0.008          -0.001   
                  (0.009)         (0.005)         (0.004)         (0.001)   
c.neg#c.ri~2        0.005           0.003           0.001           0.001   
                  (0.007)         (0.004)         (0.004)         (0.001)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.003           0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.010          -0.001          -0.002           0.004*  
                  (0.005)         (0.004)         (0.005)         (0.001)   
university          0.005           0.002          -0.002          -0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.045*          0.009          -0.007           0.001   
                  (0.021)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.091           0.072           0.000           0.045   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.010**         0.006***
                  (0.003)         (0.003)         (0.002)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001           0.001           0.001   
                  (0.004)         (0.004)         (0.002)   
c.neg#c.ri~2       -0.001           0.006          -0.000   
                  (0.003)         (0.004)         (0.002)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income             -0.008           0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.008          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.008           0.348           0.181   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.   
.   
.   replace right2= wp_right2_dicho2
(1,253,906 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.005           0.009*          0.010** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.000          -0.003          -0.015***       -0.001   
                  (0.000)         (0.002)         (0.004)         (0.002)   
c.neg#c.ri~2        0.000           0.003           0.010***       -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.008***       -0.009***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001          -0.004          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
age                 0.000**         0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.002           0.004           0.004   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.003          -0.002          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.002          -0.006           0.007   
                  (0.001)         (0.007)         (0.008)         (0.005)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.210           0.019           0.000           0.107   
r2_o                0.003           0.004           0.005           0.009   
N              666526.000       24315.000       23296.000       19125.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.005           0.005** 
                  (0.004)         (0.003)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.000          -0.001           0.000   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2       -0.002           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female              0.000           0.002          -0.001   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.002           0.005          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006**        -0.006*          0.000   
                  (0.002)         (0.002)         (0.001)   
_cons              -0.011*          0.001          -0.002   
                  (0.005)         (0.006)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.020           0.017           0.005   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012**         0.002          -0.002   
                  (0.004)         (0.002)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.001          -0.004**        -0.001   
                  (0.003)         (0.002)         (0.002)   
c.neg#c.ri~2        0.001          -0.001           0.002   
                  (0.002)         (0.001)         (0.001)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.003***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.001           0.004*          0.001   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.002   
                  (0.002)         (0.001)         (0.002)   
_cons               0.020**         0.010**        -0.001   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.009           0.004   
r2_b                0.010           0.143           0.152   
r2_o                0.007           0.006           0.003   
N               36766.000       42808.000       36042.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.007*          0.005   
                  (0.003)         (0.003)         (0.002)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001          -0.001          -0.005   
                  (0.003)         (0.002)         (0.003)   
c.neg#c.ri~2        0.002           0.001           0.003   
                  (0.002)         (0.002)         (0.002)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.000*         -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*          0.000           0.000   
                  (0.003)         (0.004)         (0.004)   
university         -0.003          -0.000           0.001   
                  (0.002)         (0.003)         (0.002)   
_cons               0.024**        -0.008           0.004   
                  (0.007)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.087           0.003           0.035   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004           0.003           0.013***        0.001   
                  (0.005)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.000           0.005*          0.003          -0.001** 
                  (0.004)         (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2        0.003           0.002           0.001           0.001*  
                  (0.003)         (0.002)         (0.002)         (0.000)   
order              -0.001**        -0.001***       -0.000          -0.000***
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.003           0.001          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.011*         -0.001          -0.003           0.004** 
                  (0.005)         (0.003)         (0.005)         (0.001)   
university          0.004           0.001          -0.002          -0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.048*          0.011*         -0.005           0.002   
                  (0.019)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.007           0.012           0.009           0.002   
r2_b                0.085           0.079           0.001           0.090   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.012***        0.006***
                  (0.003)         (0.003)         (0.001)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.000           0.001           0.002*  
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2        0.000           0.001          -0.001   
                  (0.002)         (0.002)         (0.001)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.001   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income             -0.008           0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.007          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.007           0.356           0.142   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   
.   replace right2= wp_right2_dichox
(372,030 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.005           0.007           0.008** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.000          -0.003          -0.001          -0.003   
                  (0.000)         (0.002)         (0.002)         (0.002)   
c.neg#c.ri~2        0.001*          0.002           0.004*          0.002   
                  (0.000)         (0.002)         (0.002)         (0.001)   
order              -0.000***       -0.000          -0.001***       -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.002           0.000          -0.003   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**         0.000           0.001*          0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income             -0.000           0.002           0.003           0.005   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.004          -0.004          -0.003   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.004          -0.013           0.009   
                  (0.001)         (0.007)         (0.009)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.214           0.027           0.008           0.071   
r2_o                0.003           0.004           0.005           0.009   
N              666526.000       24315.000       23296.000       19125.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.005** 
                  (0.004)         (0.003)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.001          -0.003           0.001   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2       -0.000           0.001           0.000   
                  (0.002)         (0.001)         (0.001)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female             -0.000           0.003          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.000           0.006          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006**        -0.005*          0.000   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.012*          0.001          -0.002   
                  (0.006)         (0.006)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.017           0.004           0.008   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011**         0.001          -0.001   
                  (0.004)         (0.002)         (0.002)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.003          -0.000          -0.003*  
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ri~2        0.001           0.000           0.001   
                  (0.002)         (0.001)         (0.001)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.004***       -0.004** 
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.001           0.004*          0.001   
                  (0.005)         (0.002)         (0.003)   
university         -0.002          -0.002*         -0.003   
                  (0.002)         (0.001)         (0.001)   
_cons               0.020**         0.007*         -0.000   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.008           0.004   
r2_b                0.004           0.218           0.094   
r2_o                0.007           0.006           0.003   
N               36766.000       42808.000       36042.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.007           0.005*  
                  (0.003)         (0.003)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001          -0.001          -0.000   
                  (0.001)         (0.002)         (0.001)   
c.neg#c.ri~2        0.001           0.001          -0.001   
                  (0.001)         (0.002)         (0.001)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.001*         -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*         -0.000          -0.001   
                  (0.003)         (0.004)         (0.004)   
university         -0.003          -0.000           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.024***       -0.005           0.003   
                  (0.007)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.081           0.001           0.060   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003           0.004           0.013***        0.002*  
                  (0.005)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.002           0.003           0.002           0.000   
                  (0.003)         (0.002)         (0.002)         (0.000)   
c.neg#c.ri~2        0.002          -0.001           0.002          -0.000   
                  (0.002)         (0.002)         (0.002)         (0.000)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.001          -0.005*          0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.010          -0.002          -0.002           0.003*  
                  (0.005)         (0.003)         (0.005)         (0.001)   
university          0.005           0.002          -0.002           0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.041*          0.011*         -0.004           0.001   
                  (0.020)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.007           0.012           0.009           0.002   
r2_b                0.091           0.066           0.004           0.037   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.012***        0.005***
                  (0.003)         (0.003)         (0.001)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.002           0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2       -0.001           0.000           0.001   
                  (0.001)         (0.001)         (0.001)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000*          0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income             -0.007           0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.007          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.026           0.361           0.166   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   
.   replace right2= left_right2
(1,239,431 real changes made, 1,364 to missing)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.008           0.006           0.010** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.001          -0.006          -0.012*         -0.010** 
                  (0.001)         (0.004)         (0.006)         (0.003)   
c.neg#c.ri~2        0.000          -0.004           0.011*         -0.002   
                  (0.001)         (0.003)         (0.005)         (0.003)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001           0.000          -0.002   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**        -0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.004           0.004           0.006   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.004          -0.004          -0.003   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.006          -0.008           0.013*  
                  (0.001)         (0.007)         (0.009)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.212           0.027           0.001           0.020   
r2_o                0.003           0.004           0.005           0.009   
N              665849.000       24315.000       23296.000       19125.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011**         0.001           0.006** 
                  (0.004)         (0.004)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.007          -0.012**         0.002   
                  (0.005)         (0.004)         (0.002)   
c.neg#c.ri~2        0.004           0.008*         -0.002   
                  (0.004)         (0.004)         (0.002)   
order              -0.000*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female              0.001           0.003          -0.001   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.004           0.003          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006**        -0.005           0.000   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.009           0.008          -0.003   
                  (0.006)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.005           0.001           0.005   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.001           0.002   
                  (0.004)         (0.002)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.007           0.003          -0.006** 
                  (0.004)         (0.002)         (0.002)   
c.neg#c.ri~2        0.003           0.002          -0.004*  
                  (0.004)         (0.002)         (0.002)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.004          -0.003***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.003          -0.001   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.001          -0.002   
                  (0.002)         (0.001)         (0.001)   
_cons               0.017*          0.005           0.004   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.009           0.004   
r2_b                0.002           0.162           0.015   
r2_o                0.007           0.006           0.003   
N               36766.000       42131.000       36042.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.010*          0.006*  
                  (0.003)         (0.004)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.004           0.003           0.005   
                  (0.003)         (0.004)         (0.003)   
c.neg#c.ri~2        0.001          -0.004          -0.003   
                  (0.002)         (0.003)         (0.003)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.003*  
                  (0.001)         (0.002)         (0.001)   
age                -0.000*         -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*         -0.000          -0.001   
                  (0.003)         (0.004)         (0.004)   
university         -0.003          -0.001           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.024***       -0.008          -0.000   
                  (0.007)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.081           0.001           0.054   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004          -0.001           0.017***        0.002*  
                  (0.006)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.002           0.001           0.006          -0.001   
                  (0.008)         (0.005)         (0.006)         (0.001)   
c.neg#c.ri~2        0.001           0.010**        -0.005           0.000   
                  (0.008)         (0.004)         (0.005)         (0.001)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.002***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.005*          0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000** 
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.011*         -0.003          -0.001           0.004** 
                  (0.005)         (0.003)         (0.005)         (0.001)   
university          0.005           0.003          -0.002           0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.052**         0.012*         -0.006           0.001   
                  (0.019)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.084           0.108           0.007           0.073   
r2_o                0.006           0.011           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.004           0.012**         0.006***
                  (0.003)         (0.004)         (0.002)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.004           0.006           0.002   
                  (0.004)         (0.005)         (0.001)   
c.neg#c.ri~2        0.002           0.001          -0.000   
                  (0.003)         (0.004)         (0.001)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.003*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000*          0.000           0.000** 
                  (0.000)         (0.000)         (0.000)   
income             -0.006          -0.000           0.000   
                  (0.005)         (0.003)         (0.001)   
university          0.003           0.002           0.001   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.005          -0.009***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.021           0.327           0.167   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   
.   replace right2= left_right2_dichox
(1,185,562 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.007           0.009*          0.009** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.000          -0.002          -0.004          -0.004** 
                  (0.000)         (0.002)         (0.002)         (0.002)   
c.neg#c.ri~2        0.000          -0.001           0.000           0.001   
                  (0.000)         (0.002)         (0.002)         (0.001)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001          -0.000          -0.001   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**         0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.002           0.004           0.006   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.003          -0.004          -0.003   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.004          -0.007           0.010   
                  (0.001)         (0.007)         (0.009)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.212           0.017           0.001           0.053   
r2_o                0.003           0.004           0.004           0.009   
N              665849.000       24315.000       23296.000       19125.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012**         0.005           0.005** 
                  (0.004)         (0.003)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.005*         -0.003           0.000   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2        0.003           0.002          -0.001   
                  (0.002)         (0.001)         (0.001)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female              0.002           0.003          -0.001   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.006           0.005          -0.000   
                  (0.005)         (0.004)         (0.002)   
university          0.006**        -0.006*          0.000   
                  (0.002)         (0.002)         (0.001)   
_cons              -0.009           0.001          -0.002   
                  (0.006)         (0.006)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.000           0.006           0.005   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011**         0.001           0.000   
                  (0.004)         (0.002)         (0.002)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000          -0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.004           0.002*         -0.004***
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ri~2        0.001           0.001          -0.001   
                  (0.002)         (0.001)         (0.001)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.003**        -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.003          -0.000   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.001          -0.002   
                  (0.002)         (0.001)         (0.001)   
_cons               0.018**         0.006*          0.001   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.009           0.004   
r2_b                0.000           0.149           0.010   
r2_o                0.007           0.006           0.003   
N               36766.000       42131.000       36042.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.008*          0.005   
                  (0.003)         (0.003)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.004**         0.001           0.001   
                  (0.001)         (0.002)         (0.001)   
c.neg#c.ri~2        0.001          -0.003          -0.000   
                  (0.001)         (0.002)         (0.001)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.005***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.006*         -0.000          -0.001   
                  (0.003)         (0.004)         (0.004)   
university         -0.002          -0.001           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.022***       -0.007           0.001   
                  (0.007)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.046           0.001           0.064   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004           0.001           0.016***        0.002   
                  (0.005)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.004***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.000          -0.001           0.004*         -0.000   
                  (0.003)         (0.002)         (0.002)         (0.000)   
c.neg#c.ri~2        0.001           0.004*         -0.002           0.001   
                  (0.002)         (0.002)         (0.002)         (0.000)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.006*          0.001          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.011*         -0.003           0.000           0.003*  
                  (0.005)         (0.003)         (0.005)         (0.001)   
university          0.005           0.003          -0.002           0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.050**         0.013*         -0.006           0.001   
                  (0.018)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.086           0.100           0.002           0.047   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.004           0.012***        0.006***
                  (0.003)         (0.003)         (0.001)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003           0.005**         0.001   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2        0.002           0.001           0.000   
                  (0.001)         (0.001)         (0.001)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.003           0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000*          0.000           0.000** 
                  (0.000)         (0.000)         (0.000)   
income             -0.006          -0.002           0.000   
                  (0.005)         (0.003)         (0.001)   
university          0.002           0.003           0.001   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.005          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.045           0.149           0.165   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   
.   replace right2= ideo_right2
(1,309,786 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.006           0.006           0.010** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.000          -0.010*         -0.012*         -0.010** 
                  (0.001)         (0.005)         (0.006)         (0.004)   
c.neg#c.ri~2        0.001          -0.000           0.013*         -0.002   
                  (0.001)         (0.004)         (0.005)         (0.003)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001           0.000          -0.002   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**        -0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.004           0.003           0.005   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.004          -0.004          -0.003   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.007          -0.008           0.011*  
                  (0.001)         (0.007)         (0.009)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.214           0.080           0.000           0.032   
r2_o                0.003           0.004           0.005           0.009   
N              665849.000       24315.000       23296.000       19125.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012**         0.001           0.005** 
                  (0.004)         (0.005)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003          -0.019**         0.003   
                  (0.006)         (0.007)         (0.003)   
c.neg#c.ri~2        0.003           0.009          -0.001   
                  (0.004)         (0.006)         (0.002)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female              0.000           0.003          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.003           0.004          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006**        -0.004           0.001   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.010           0.010          -0.003   
                  (0.006)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.015           0.001           0.008   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*         -0.001           0.001   
                  (0.005)         (0.003)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.008           0.003          -0.014***
                  (0.005)         (0.004)         (0.004)   
c.neg#c.ri~2        0.004           0.004          -0.003   
                  (0.005)         (0.004)         (0.003)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.004***       -0.002   
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.004          -0.003   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.003*  
                  (0.002)         (0.001)         (0.001)   
_cons               0.017*          0.006           0.008   
                  (0.007)         (0.004)         (0.005)   
------------------------------------------------------------
r2_w                0.009           0.009           0.004   
r2_b                0.003           0.195           0.002   
r2_o                0.007           0.006           0.003   
N               36766.000       42131.000       36042.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.004           0.007           0.006*  
                  (0.003)         (0.007)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.008           0.007           0.003   
                  (0.005)         (0.011)         (0.004)   
c.neg#c.ri~2        0.006           0.000          -0.003   
                  (0.005)         (0.010)         (0.003)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004*  
                  (0.001)         (0.002)         (0.001)   
age                -0.001*         -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*          0.001          -0.001   
                  (0.003)         (0.005)         (0.004)   
university         -0.003          -0.001           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.027***       -0.011           0.001   
                  (0.007)         (0.012)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.080           0.002           0.065   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.001           0.015**         0.002   
                  (0.006)         (0.004)         (0.005)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.000           0.006           0.014          -0.002   
                  (0.010)         (0.006)         (0.007)         (0.001)   
c.neg#c.ri~2        0.004           0.008          -0.002           0.001   
                  (0.009)         (0.004)         (0.006)         (0.001)   
order              -0.001**        -0.001***       -0.000          -0.000***
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.002***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.004           0.001          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000** 
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.011*         -0.002          -0.000           0.004** 
                  (0.005)         (0.003)         (0.005)         (0.001)   
university          0.005           0.002          -0.002          -0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.049*          0.010          -0.009           0.001   
                  (0.021)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.089           0.103           0.000           0.076   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.004           0.011**         0.006***
                  (0.003)         (0.004)         (0.002)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003           0.004           0.002   
                  (0.004)         (0.005)         (0.002)   
c.neg#c.ri~2        0.001           0.005          -0.000   
                  (0.003)         (0.004)         (0.002)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000** 
                  (0.000)         (0.000)         (0.000)   
income             -0.007          -0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.006          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.013           0.333           0.173   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   
.   replace right2= ideo_right2_dichox
(1,309,786 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.007           0.008*          0.009** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.001*         -0.003          -0.003          -0.004** 
                  (0.000)         (0.002)         (0.002)         (0.002)   
c.neg#c.ri~2        0.001***       -0.002           0.003           0.001   
                  (0.000)         (0.002)         (0.002)         (0.001)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001           0.001          -0.001   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**         0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.001           0.002           0.005   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.004          -0.003          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.004          -0.010           0.009   
                  (0.001)         (0.007)         (0.009)         (0.005)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.207           0.012           0.000           0.032   
r2_o                0.003           0.004           0.004           0.009   
N              665849.000       24315.000       23296.000       19125.000   
N_g               932.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012**         0.006           0.005*  
                  (0.004)         (0.003)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.006**        -0.005**         0.001   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2        0.002           0.001           0.001   
                  (0.002)         (0.001)         (0.001)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female              0.002           0.003          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.008           0.006          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.005**        -0.005*          0.000   
                  (0.002)         (0.002)         (0.001)   
_cons              -0.009           0.004          -0.002   
                  (0.005)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.002           0.003           0.017   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011**         0.001           0.000   
                  (0.004)         (0.002)         (0.002)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.004           0.001          -0.005***
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ri~2        0.001           0.001          -0.001   
                  (0.002)         (0.001)         (0.001)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.004***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.004*         -0.003   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.003   
                  (0.002)         (0.001)         (0.001)   
_cons               0.018**         0.007*          0.000   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.009           0.004   
r2_b                0.000           0.195           0.002   
r2_o                0.007           0.006           0.003   
N               36766.000       42131.000       36042.000   
N_g                51.000          59.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.007*          0.005   
                  (0.003)         (0.004)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003*          0.000           0.001   
                  (0.001)         (0.002)         (0.001)   
c.neg#c.ri~2        0.001           0.000          -0.000   
                  (0.001)         (0.002)         (0.001)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004*  
                  (0.001)         (0.002)         (0.001)   
age                -0.000*         -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*          0.000          -0.001   
                  (0.003)         (0.004)         (0.004)   
university         -0.003          -0.000           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.025***       -0.008           0.001   
                  (0.007)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.050           0.003           0.065   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.001           0.014***        0.002   
                  (0.005)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.003           0.002           0.003          -0.001   
                  (0.003)         (0.002)         (0.002)         (0.000)   
c.neg#c.ri~2        0.005*          0.004*          0.001           0.001   
                  (0.002)         (0.002)         (0.002)         (0.000)   
order              -0.001**        -0.001***       -0.000          -0.000***
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.003          -0.004           0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.011*         -0.003          -0.002           0.004*  
                  (0.005)         (0.003)         (0.005)         (0.001)   
university          0.005           0.003          -0.002           0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.055**         0.010          -0.004           0.001   
                  (0.019)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.007           0.012           0.009           0.002   
r2_b                0.052           0.105           0.007           0.049   
r2_o                0.006           0.011           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.004           0.011**         0.006***
                  (0.003)         (0.003)         (0.001)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003           0.003*          0.001   
                  (0.002)         (0.002)         (0.001)   
c.neg#c.ri~2        0.002           0.003*          0.000   
                  (0.001)         (0.001)         (0.001)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.003*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000*          0.000           0.000** 
                  (0.000)         (0.000)         (0.000)   
income             -0.006          -0.000           0.000   
                  (0.005)         (0.003)         (0.001)   
university          0.002           0.002           0.001   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.006          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.045           0.213           0.163   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.  
.   
. * Table A8 Row 3 
.  
.   replace right2= wp_right2  
(1,265,458 real changes made)
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 &amp; wp_right2_ext==1, re
&gt;   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 &amp; political_interest_d
&gt; ichox==1, re  
.   estimates store C
.   esttab A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r
&gt; 2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.005***        0.005***        0.003** 
                  (0.001)         (0.001)         (0.001)   
timesecSto~g       -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
c.neg#c.ti~g       -0.001***       -0.002***       -0.001***
                  (0.000)         (0.000)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.001           0.001           0.002   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ri~2        0.001           0.002*          0.002** 
                  (0.001)         (0.001)         (0.001)   
order              -0.000***       -0.000***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.008***       -0.009***
                  (0.000)         (0.000)         (0.000)   
female             -0.001*         -0.000          -0.001   
                  (0.000)         (0.000)         (0.000)   
age                 0.000**         0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.000           0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
university         -0.000           0.000          -0.001*  
                  (0.000)         (0.000)         (0.001)   
_cons               0.001          -0.001           0.003*  
                  (0.001)         (0.001)         (0.002)   
------------------------------------------------------------
r2_w                0.005           0.005           0.005   
r2_b                0.211           0.225           0.242   
r2_o                0.003           0.003           0.004   
N              666526.000      360355.000      317613.000   
N_g               933.000         505.000         444.000   
------------------------------------------------------------
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.003           0.007           0.010** 
                  (0.001)         (0.004)         (0.004)         (0.003)   
timesecSto~g       -0.000          -0.002           0.000          -0.002*  
                  (0.000)         (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001          -0.002*         -0.003***
                  (0.000)         (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.001          -0.013*         -0.009          -0.008*  
                  (0.001)         (0.005)         (0.006)         (0.004)   
c.neg#c.ri~2        0.001           0.008           0.011*         -0.001   
                  (0.001)         (0.005)         (0.005)         (0.003)   
order              -0.000***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.009***       -0.008***       -0.017***
                  (0.000)         (0.001)         (0.001)         (0.001)   
female             -0.001*         -0.001           0.000          -0.002   
                  (0.000)         (0.002)         (0.002)         (0.002)   
age                 0.000**         0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income              0.000           0.002           0.003           0.005   
                  (0.001)         (0.005)         (0.004)         (0.004)   
university         -0.000           0.003          -0.003          -0.002   
                  (0.000)         (0.002)         (0.003)         (0.002)   
_cons               0.001           0.007          -0.010           0.009   
                  (0.001)         (0.007)         (0.008)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.006           0.012   
r2_b                0.211           0.097           0.002           0.056   
r2_o                0.003           0.004           0.005           0.009   
N              666526.000       24315.000       23296.000       19125.000   
N_g               933.000          35.000          32.000          27.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.006           0.005*  
                  (0.004)         (0.004)         (0.002)   
timesecSto~g        0.002          -0.000          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003***       -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005           0.003   
                  (0.005)         (0.006)         (0.003)   
c.neg#c.ri~2       -0.001          -0.000           0.001   
                  (0.004)         (0.005)         (0.002)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.007***       -0.009***       -0.004***
                  (0.001)         (0.001)         (0.001)   
female             -0.000           0.002          -0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.000           0.005          -0.001   
                  (0.005)         (0.004)         (0.002)   
university          0.006***       -0.005*          0.001   
                  (0.002)         (0.003)         (0.001)   
_cons              -0.014*          0.002          -0.003   
                  (0.006)         (0.007)         (0.003)   
------------------------------------------------------------
r2_w                0.006           0.004           0.002   
r2_b                0.015           0.014           0.015   
r2_o                0.004           0.004           0.002   
N               26102.000       40263.000       24849.000   
N_g                36.000          56.000          35.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 , r
&gt; e 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 , r
&gt; e  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.001          -0.002   
                  (0.004)         (0.002)         (0.003)   
timesecSto~g       -0.003**        -0.002**         0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.005          -0.005          -0.007*  
                  (0.006)         (0.003)         (0.003)   
c.neg#c.ri~2        0.004           0.001           0.002   
                  (0.005)         (0.002)         (0.002)   
order              -0.001***       -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.013***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.003          -0.003***       -0.003*  
                  (0.002)         (0.001)         (0.001)   
age                -0.000           0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.002           0.004*          0.000   
                  (0.005)         (0.002)         (0.003)   
university         -0.001          -0.002          -0.003   
                  (0.002)         (0.001)         (0.002)   
_cons               0.019**         0.009**         0.003   
                  (0.007)         (0.003)         (0.004)   
------------------------------------------------------------
r2_w                0.009           0.008           0.004   
r2_b                0.005           0.180           0.083   
r2_o                0.007           0.006           0.003   
N               36766.000       42808.000       36042.000   
N_g                51.000          60.000          50.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.002           0.005           0.005   
                  (0.003)         (0.004)         (0.003)   
timesecSto~g       -0.001           0.003***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.000          -0.002*         -0.001*  
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001          -0.003          -0.003   
                  (0.004)         (0.005)         (0.004)   
c.neg#c.ri~2        0.003           0.006          -0.000   
                  (0.003)         (0.004)         (0.004)   
order              -0.001***       -0.000          -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.004***       -0.003***       -0.016***
                  (0.001)         (0.001)         (0.001)   
female             -0.002           0.002          -0.004** 
                  (0.001)         (0.002)         (0.001)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.007*         -0.000          -0.000   
                  (0.003)         (0.005)         (0.004)   
university         -0.003          -0.000           0.002   
                  (0.002)         (0.003)         (0.002)   
_cons               0.023**        -0.005           0.003   
                  (0.008)         (0.011)         (0.006)   
------------------------------------------------------------
r2_w                0.003           0.002           0.010   
r2_b                0.088           0.001           0.058   
r2_o                0.002           0.002           0.008   
N               51367.000       22728.000       26122.000   
N_g                71.000          32.000          37.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 , re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 , re 
&gt;  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.003           0.013**         0.001   
                  (0.006)         (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.004**        -0.001          -0.000          -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.003***       -0.001** 
                  (0.001)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.003           0.010           0.008          -0.001   
                  (0.009)         (0.005)         (0.004)         (0.001)   
c.neg#c.ri~2        0.005           0.003           0.001           0.001   
                  (0.007)         (0.004)         (0.004)         (0.001)   
order              -0.001**        -0.001***       -0.000          -0.000** 
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.021***       -0.014***       -0.003***
                  (0.001)         (0.001)         (0.001)         (0.001)   
female             -0.002          -0.003           0.002          -0.001** 
                  (0.003)         (0.002)         (0.002)         (0.000)   
age                -0.001          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income             -0.010          -0.001          -0.002           0.004*  
                  (0.005)         (0.004)         (0.005)         (0.001)   
university          0.005           0.002          -0.002          -0.000   
                  (0.004)         (0.002)         (0.003)         (0.000)   
_cons               0.045*          0.009          -0.007           0.001   
                  (0.021)         (0.006)         (0.007)         (0.002)   
----------------------------------------------------------------------------
r2_w                0.006           0.012           0.009           0.002   
r2_b                0.091           0.072           0.000           0.045   
r2_o                0.006           0.010           0.008           0.002   
N               25380.000       23150.000       22867.000       33376.000   
N_g                36.000          32.000          32.000          48.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.003           0.010**         0.006***
                  (0.003)         (0.003)         (0.002)   
timesecSto~g       -0.001          -0.001           0.001***
                  (0.001)         (0.001)         (0.000)   
c.neg#c.ti~g        0.000          -0.003***       -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.001           0.001           0.001   
                  (0.004)         (0.004)         (0.002)   
c.neg#c.ri~2       -0.001           0.006          -0.000   
                  (0.003)         (0.004)         (0.002)   
order              -0.000          -0.001**        -0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.012***       -0.006***
                  (0.001)         (0.001)         (0.000)   
female              0.003          -0.004*          0.000   
                  (0.002)         (0.002)         (0.001)   
age                 0.000           0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
income             -0.008           0.000           0.000   
                  (0.004)         (0.003)         (0.001)   
university          0.002           0.002           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.001           0.008          -0.008***
                  (0.005)         (0.005)         (0.002)   
------------------------------------------------------------
r2_w                0.006           0.008           0.004   
r2_b                0.008           0.348           0.181   
r2_o                0.006           0.005           0.002   
N               22094.000       35294.000      130582.000   
N_g                31.000          48.000         184.000   
------------------------------------------------------------
.     
.         
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 &amp; wp_right2_ext==1, re
&gt;   
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 &amp; w
&gt; p_right2_ext==1, re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 &amp; w
&gt; p_right2_ext==1, re  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store F 
.   esttab G A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005***        0.008           0.015*          0.009*  
                  (0.001)         (0.005)         (0.007)         (0.004)   
timesecSto~g       -0.000          -0.003*          0.002          -0.001   
                  (0.000)         (0.001)         (0.002)         (0.001)   
c.neg#c.ti~g       -0.002***       -0.003*         -0.004*         -0.003** 
                  (0.000)         (0.001)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.001          -0.014**        -0.005          -0.007   
                  (0.001)         (0.005)         (0.008)         (0.004)   
c.neg#c.ri~2        0.002*          0.008           0.009          -0.001   
                  (0.001)         (0.005)         (0.006)         (0.003)   
order              -0.000***       -0.000          -0.002***       -0.001*  
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.008***       -0.006***       -0.009***       -0.014***
                  (0.000)         (0.001)         (0.001)         (0.002)   
female             -0.000          -0.003           0.004          -0.000   
                  (0.000)         (0.003)         (0.004)         (0.003)   
age                 0.000*         -0.000           0.002**         0.000   
                  (0.000)         (0.000)         (0.001)         (0.000)   
income              0.001           0.009           0.000           0.008   
                  (0.001)         (0.008)         (0.007)         (0.005)   
university          0.000           0.003          -0.006          -0.002   
                  (0.000)         (0.003)         (0.006)         (0.002)   
_cons              -0.001           0.019*         -0.037*          0.006   
                  (0.001)         (0.010)         (0.017)         (0.007)   
----------------------------------------------------------------------------
r2_w                0.005           0.003           0.008           0.010   
r2_b                0.225           0.423           0.018           0.197   
r2_o                0.003           0.003           0.006           0.007   
N              360355.000       12097.000       11669.000       11212.000   
N_g               505.000          17.000          16.000          16.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010**         0.010*         -0.003   
                  (0.004)         (0.004)         (0.003)   
timesecSto~g        0.001          -0.001          -0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.003**        -0.003**         0.000   
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.016***       -0.007           0.003   
                  (0.005)         (0.007)         (0.004)   
c.neg#c.ri~2       -0.003           0.000           0.003   
                  (0.003)         (0.005)         (0.002)   
order              -0.001*         -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.006***       -0.010***       -0.010***
                  (0.001)         (0.001)         (0.001)   
female              0.001           0.004          -0.000   
                  (0.002)         (0.002)         (0.002)   
age                 0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.014*          0.005          -0.004   
                  (0.006)         (0.005)         (0.004)   
university          0.010***       -0.004           0.002   
                  (0.002)         (0.004)         (0.002)   
_cons              -0.027***        0.002          -0.002   
                  (0.007)         (0.008)         (0.005)   
------------------------------------------------------------
r2_w                0.006           0.005           0.005   
r2_b                0.126           0.010           0.032   
r2_o                0.005           0.005           0.005   
N               13657.000       30367.000       12762.000   
N_g                19.000          42.000          18.000   
------------------------------------------------------------
.     
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 &amp; w
&gt; p_right2_ext==1, re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 &amp; w
&gt; p_right2_ext==1, re  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.018**         0.001           0.001   
                  (0.006)         (0.003)         (0.004)   
timesecSto~g       -0.004*         -0.002*          0.001   
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.005**        -0.000          -0.001   
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.016          -0.006*         -0.012** 
                  (0.009)         (0.003)         (0.004)   
c.neg#c.ri~2        0.005           0.001           0.001   
                  (0.005)         (0.002)         (0.003)   
order              -0.001*         -0.001***       -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.013***       -0.009***
                  (0.001)         (0.001)         (0.001)   
female             -0.007*         -0.002          -0.001   
                  (0.003)         (0.001)         (0.002)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.017*          0.004*         -0.011*  
                  (0.008)         (0.002)         (0.005)   
university         -0.001           0.001          -0.000   
                  (0.003)         (0.001)         (0.002)   
_cons               0.015           0.009*          0.010   
                  (0.010)         (0.004)         (0.007)   
------------------------------------------------------------
r2_w                0.009           0.008           0.006   
r2_b                0.019           0.012           0.096   
r2_o                0.008           0.006           0.004   
N               16651.000       23760.000       19926.000   
N_g                23.000          33.000          28.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.001           0.002           0.002   
                  (0.003)         (0.006)         (0.004)   
timesecSto~g        0.001           0.005***        0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.000          -0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.004          -0.002          -0.001   
                  (0.005)         (0.006)         (0.005)   
c.neg#c.ri~2        0.004           0.006           0.001   
                  (0.003)         (0.005)         (0.004)   
order              -0.000*         -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.002***       -0.003*         -0.020***
                  (0.001)         (0.001)         (0.002)   
female              0.001           0.001          -0.007***
                  (0.002)         (0.003)         (0.002)   
age                -0.000          -0.000          -0.001   
                  (0.000)         (0.002)         (0.000)   
income             -0.003           0.001           0.010   
                  (0.005)         (0.010)         (0.005)   
university          0.001           0.001           0.011*  
                  (0.003)         (0.007)         (0.005)   
_cons               0.001          -0.017          -0.000   
                  (0.011)         (0.034)         (0.014)   
------------------------------------------------------------
r2_w                0.001           0.003           0.012   
r2_b                0.001           0.023           0.007   
r2_o                0.001           0.002           0.011   
N               29739.000       11375.000       13141.000   
N_g                42.000          16.000          19.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 &amp; wp_
&gt; right2_ext==1, re  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.005           0.010           0.003   
                  (0.009)         (0.004)         (0.006)         (0.002)   
timesecSto~g       -0.005*         -0.001           0.003          -0.001*  
                  (0.002)         (0.001)         (0.002)         (0.000)   
c.neg#c.ti~g       -0.001          -0.001          -0.002          -0.001** 
                  (0.002)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2             -0.001           0.010           0.006          -0.002   
                  (0.012)         (0.006)         (0.006)         (0.002)   
c.neg#c.ri~2        0.005           0.002           0.001           0.002   
                  (0.008)         (0.004)         (0.005)         (0.001)   
order              -0.001          -0.000          -0.001          -0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.019***       -0.020***       -0.016***       -0.004***
                  (0.002)         (0.002)         (0.002)         (0.001)   
female              0.002          -0.000           0.003          -0.001   
                  (0.005)         (0.003)         (0.003)         (0.001)   
age                -0.003          -0.000           0.000           0.000   
                  (0.002)         (0.000)         (0.000)         (0.000)   
income             -0.008          -0.005           0.001           0.003   
                  (0.008)         (0.005)         (0.007)         (0.002)   
university          0.017           0.007*         -0.022*         -0.000   
                  (0.011)         (0.003)         (0.009)         (0.001)   
_cons               0.071*          0.006           0.000           0.004   
                  (0.035)         (0.007)             (.)         (0.003)   
----------------------------------------------------------------------------
r2_w                0.009           0.012           0.011           0.002   
r2_b                0.035           0.009           0.044           0.084   
r2_o                0.009           0.010           0.010           0.002   
N               12381.000       13628.000       12261.000       17370.000   
N_g                17.000          19.000          17.000          25.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.000          -0.002           0.006** 
                  (0.003)         (0.003)         (0.002)   
timesecSto~g       -0.002**        -0.001           0.000   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.000          -0.000          -0.002***
                  (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.003          -0.007           0.001   
                  (0.003)         (0.004)         (0.002)   
c.neg#c.ri~2       -0.001           0.007*         -0.001   
                  (0.002)         (0.003)         (0.002)   
order              -0.000          -0.000*         -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015***       -0.011***       -0.007***
                  (0.002)         (0.001)         (0.001)   
female              0.001          -0.004*          0.001   
                  (0.003)         (0.002)         (0.001)   
age                -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.012*          0.012**         0.001   
                  (0.005)         (0.004)         (0.002)   
university         -0.000           0.003           0.000   
                  (0.002)         (0.002)         (0.001)   
_cons               0.017*          0.001          -0.003   
                  (0.007)         (0.005)         (0.003)   
------------------------------------------------------------
r2_w                0.009           0.008           0.004   
r2_b                0.010           0.081           0.229   
r2_o                0.008           0.006           0.003   
N               10559.000       17812.000       69988.000   
N_g                15.000          24.000          99.000   
------------------------------------------------------------
.  
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 0 to 1629
                delta:  1 unit
.   replace neg = negativity
(0 real changes made)
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; local==0 &amp; political_interest_d
&gt; ichox==1, re  
.   estimates store G  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.e&quot; &amp; period==2 &amp; local==0 &amp; p
&gt; olitical_interest_dichox==1, re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; local==0 &amp; p
&gt; olitical_interest_dichox==1, re  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store F 
.   esttab G A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b
&gt;  r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003**         0.002          -0.004           0.010** 
                  (0.001)         (0.007)         (0.008)         (0.003)   
timesecSto~g       -0.000          -0.002           0.003          -0.002*  
                  (0.000)         (0.002)         (0.002)         (0.001)   
c.neg#c.ti~g       -0.001***       -0.001           0.001          -0.003***
                  (0.000)         (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.002          -0.013           0.028          -0.008   
                  (0.001)         (0.009)         (0.028)         (0.004)   
c.neg#c.ri~2        0.002**         0.009          -0.023          -0.001   
                  (0.001)         (0.007)         (0.024)         (0.004)   
order              -0.001***       -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.009***       -0.009***       -0.007***       -0.017***
                  (0.000)         (0.001)         (0.002)         (0.001)   
female             -0.001           0.002          -0.004          -0.004   
                  (0.000)         (0.004)         (0.005)         (0.002)   
age                 0.000           0.000           0.001           0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
income             -0.001           0.006           0.002           0.003   
                  (0.001)         (0.008)         (0.009)         (0.004)   
university         -0.001*          0.004           0.009          -0.002   
                  (0.001)         (0.004)         (0.010)         (0.002)   
_cons               0.003*          0.007          -0.029           0.010   
                  (0.002)         (0.012)         (0.021)         (0.006)   
----------------------------------------------------------------------------
r2_w                0.005           0.004           0.004           0.012   
r2_b                0.242           0.048           0.137           0.033   
r2_o                0.004           0.004           0.004           0.009   
N              317613.000       13363.000        8104.000       17783.000   
N_g               444.000          19.000          11.000          25.000   
----------------------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.018**         0.002           0.006*  
                  (0.007)         (0.004)         (0.003)   
timesecSto~g        0.001          -0.000          -0.002*  
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.005**        -0.001          -0.001*  
                  (0.002)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.003           0.010           0.009*  
                  (0.009)         (0.007)         (0.004)   
c.neg#c.ri~2        0.003           0.001           0.002   
                  (0.007)         (0.006)         (0.003)   
order              -0.001**        -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.010***       -0.010***       -0.007***
                  (0.001)         (0.001)         (0.001)   
female             -0.008          -0.003           0.003   
                  (0.004)         (0.002)         (0.002)   
age                 0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.041**         0.002          -0.001   
                  (0.015)         (0.005)         (0.003)   
university          0.007          -0.008**         0.003*  
                  (0.005)         (0.003)         (0.002)   
_cons               0.006           0.009          -0.002   
                  (0.012)         (0.008)         (0.004)   
------------------------------------------------------------
r2_w                0.006           0.005           0.005   
r2_b                0.010           0.021           0.167   
r2_o                0.005           0.004           0.005   
N               10828.000       28830.000       11162.000   
N_g                15.000          40.000          16.000   
------------------------------------------------------------
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; local==0 &amp; p
&gt; olitical_interest_dichox==1, re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; local==0 &amp; p
&gt; olitical_interest_dichox==1, re  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store F 
.   esttab A B C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.002          -0.003           0.001   
                  (0.006)         (0.003)         (0.005)   
timesecSto~g       -0.006***       -0.001           0.001   
                  (0.002)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.001           0.001          -0.001   
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.027*         -0.005          -0.007   
                  (0.011)         (0.003)         (0.004)   
c.neg#c.ri~2        0.005          -0.001           0.006   
                  (0.007)         (0.003)         (0.004)   
order              -0.001*         -0.000**        -0.001***
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.013***       -0.009***       -0.010***
                  (0.002)         (0.001)         (0.001)   
female             -0.002          -0.002           0.000   
                  (0.003)         (0.001)         (0.003)   
age                 0.000           0.000**        -0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.005           0.008***        0.004   
                  (0.007)         (0.002)         (0.005)   
university          0.000          -0.001          -0.004   
                  (0.003)         (0.001)         (0.002)   
_cons               0.033**        -0.003           0.008   
                  (0.010)         (0.005)         (0.007)   
------------------------------------------------------------
r2_w                0.008           0.005           0.006   
r2_b                0.060           0.063           0.187   
r2_o                0.007           0.005           0.004   
N               12957.000       19843.000       19051.000   
N_g                18.000          28.000          26.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                -0.006          -0.001           0.012** 
                  (0.004)         (0.006)         (0.004)   
timesecSto~g       -0.001           0.003*          0.001   
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g        0.001          -0.002          -0.003** 
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.004           0.010           0.008   
                  (0.006)         (0.009)         (0.008)   
c.neg#c.ri~2        0.008           0.017*         -0.002   
                  (0.005)         (0.008)         (0.006)   
order              -0.001***       -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.006***       -0.003**        -0.014***
                  (0.001)         (0.001)         (0.002)   
female             -0.001           0.003          -0.002   
                  (0.002)         (0.003)         (0.002)   
age                -0.001          -0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.012**        -0.001           0.001   
                  (0.004)         (0.007)         (0.007)   
university         -0.005*         -0.004          -0.001   
                  (0.003)         (0.006)         (0.004)   
_cons               0.031**        -0.005           0.001   
                  (0.010)         (0.015)         (0.009)   
------------------------------------------------------------
r2_w                0.005           0.002           0.008   
r2_b                0.115           0.043           0.017   
r2_o                0.002           0.002           0.008   
N               33832.000       13226.000        9546.000   
N_g                47.000          19.000          13.000   
------------------------------------------------------------
.  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re 
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re 
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; local==0 &amp; pol
&gt; itical_interest_dichox==1, re  
.   estimates store G 
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.002          -0.004           0.019**         0.001   
                  (0.009)         (0.005)         (0.007)         (0.002)   
timesecSto~g       -0.007**        -0.001           0.002          -0.001***
                  (0.002)         (0.001)         (0.002)         (0.000)   
c.neg#c.ti~g       -0.000           0.001          -0.004**        -0.001   
                  (0.002)         (0.001)         (0.001)         (0.000)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.002           0.008           0.017**        -0.001   
                  (0.014)         (0.006)         (0.006)         (0.002)   
c.neg#c.ri~2        0.003           0.003          -0.003           0.002   
                  (0.010)         (0.005)         (0.005)         (0.002)   
order              -0.001          -0.001***        0.000          -0.000** 
                  (0.001)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.012***       -0.026***       -0.015***       -0.003***
                  (0.002)         (0.002)         (0.002)         (0.001)   
female              0.001          -0.008**         0.003          -0.001   
                  (0.006)         (0.003)         (0.003)         (0.001)   
age                -0.002          -0.000           0.000           0.000*  
                  (0.001)         (0.000)         (0.000)         (0.000)   
income              0.001          -0.002          -0.000           0.009***
                  (0.010)         (0.005)         (0.007)         (0.003)   
university          0.070          -0.001          -0.007           0.001   
                  (0.039)         (0.003)         (0.006)         (0.001)   
_cons               0.000           0.019*         -0.024*         -0.000   
                      (.)         (0.008)         (0.012)         (0.003)   
----------------------------------------------------------------------------
r2_w                0.006           0.015           0.010           0.003   
r2_b                0.057           0.000           0.212           0.120   
r2_o                0.005           0.014           0.010           0.003   
N               12112.000       14469.000       11497.000       18203.000   
N_g                17.000          20.000          16.000          27.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.001           0.005           0.008** 
                  (0.004)         (0.005)         (0.003)   
timesecSto~g       -0.002*         -0.003           0.002*  
                  (0.001)         (0.001)         (0.001)   
c.neg#c.ti~g       -0.000          -0.002          -0.002** 
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.000          -0.011          -0.001   
                  (0.005)         (0.009)         (0.003)   
c.neg#c.ri~2       -0.000           0.001           0.000   
                  (0.004)         (0.006)         (0.003)   
order              -0.000          -0.001**        -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.019***       -0.028***       -0.011***
                  (0.002)         (0.002)         (0.001)   
female              0.005           0.001           0.001   
                  (0.003)         (0.003)         (0.001)   
age                 0.000*          0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.016*          0.009          -0.004   
                  (0.007)         (0.008)         (0.003)   
university         -0.001          -0.003           0.003*  
                  (0.003)         (0.004)         (0.002)   
_cons               0.012           0.015          -0.008   
                  (0.007)         (0.010)         (0.004)   
------------------------------------------------------------
r2_w                0.010           0.016           0.007   
r2_b                0.069           0.311           0.114   
r2_o                0.010           0.014           0.006   
N                7754.000       11734.000       43319.000   
N_g                11.000          16.000          60.000   
------------------------------------------------------------
.  
.   
.   
.   
.       </code></pre>
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</div>
<div id="analysis-of-time-series-data-photos.dta" class="section level2">
<h2>Analysis of Time-series-data-photos.dta</h2>
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<pre class="r"><code>
P$country2 &lt;- as.character(P$country2)
stata_src &lt;- readLines(&quot;Time-series-data-photos.do&quot;)
stata(stata_src,data.in=P)</code></pre>
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<!-- rnb-output-begin {"data":". *** Syntax for analyses of time-series photo data\n. *** Use data file 'Time-series-data-photos.dta' with this syntax\n. * Table 5 Columns 5 , 6 and 7\n.  \n.   gen neg = .\n(449,554 missing values generated)\n.   replace neg = negativity\n(309,058 real changes made)\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc\n> ome university if wp_right2_dichox==0 & period==2 , re  \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc\n> ome university if wp_right2_dichox==1 & period==2 , re  \n.   estimates store C\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.wp_right2 order L.g\n> slmc female age income university if period==2 , re    \n.   estimates store D  \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011***        0.007***        0.010***\n                  (0.002)         (0.002)         (0.001)   \ntimesecSto~g        0.005          -0.001           0.002   \n                  (0.005)         (0.005)         (0.004)   \nc.neg#c.ti~g       -0.005***       -0.003**        -0.004***\n                  (0.001)         (0.001)         (0.001)   \norder               0.000*          0.000           0.000*  \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.128***       -0.133***       -0.131***\n                  (0.002)         (0.002)         (0.002)   \nfemale              0.003           0.002           0.003   \n                  (0.002)         (0.002)         (0.002)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.000          -0.012*         -0.006   \n                  (0.005)         (0.005)         (0.003)   \nuniversity         -0.001           0.004           0.002   \n                  (0.002)         (0.002)         (0.002)   \nneg                                                 0.000   \n                                                      (.)   \nwp_right2                                           0.013   \n                                                  (0.008)   \nc.neg#c.wp~2                                       -0.002   \n                                                  (0.002)   \n_cons              -0.023*         -0.007          -0.020*  \n                  (0.010)         (0.010)         (0.008)   \n------------------------------------------------------------\nr2_w                0.057           0.053           0.055   \nr2_b                0.043           0.007           0.006   \nr2_o                0.054           0.052           0.053   \nN               70213.000       67823.000      138036.000   \nN_g               411.000         397.000         808.000   \n------------------------------------------------------------\n.   \n.   \n. * Table 6 Column 2\n.   \n.   gen right2 = .\n(449,554 missing values generated)\n.   replace right2= wp_right2\n(446,870 real changes made)\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store G\n.   esttab A C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014**         0.013           0.010*  \n                  (0.004)         (0.008)         (0.004)   \ntimesecSto~g        0.026*          0.031          -0.001   \n                  (0.011)         (0.023)         (0.011)   \nc.neg#c.ti~g       -0.009***       -0.006          -0.005** \n                  (0.002)         (0.005)         (0.002)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.035           0.055          -0.009   \n                  (0.033)         (0.055)         (0.028)   \nc.neg#c.ri~2        0.000          -0.002          -0.001   \n                  (0.006)         (0.011)         (0.005)   \norder               0.000           0.001           0.000   \n                  (0.000)         (0.001)         (0.000)   \nL.gslmc            -0.028***       -0.186***       -0.021***\n                  (0.005)         (0.009)         (0.004)   \nfemale              0.005           0.013           0.005   \n                  (0.006)         (0.012)         (0.005)   \nage                -0.000          -0.000           0.000   \n                  (0.001)         (0.000)         (0.000)   \nincome             -0.001          -0.048*         -0.015   \n                  (0.014)         (0.024)         (0.014)   \nuniversity         -0.001           0.040**        -0.003   \n                  (0.006)         (0.013)         (0.005)   \n_cons              -0.032          -0.096          -0.003   \n                  (0.028)         (0.050)         (0.024)   \n------------------------------------------------------------\nr2_w                0.010           0.092           0.011   \nr2_b                0.137           0.023           0.096   \nr2_o                0.011           0.088           0.011   \nN                5607.000        4617.000        6156.000   \nN_g                33.000          27.000          36.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.008           0.000           0.004   \n                  (0.004)         (0.002)         (0.004)   \ntimesecSto~g        0.011          -0.001          -0.015   \n                  (0.009)         (0.005)         (0.011)   \nc.neg#c.ti~g       -0.006***       -0.001          -0.000   \n                  (0.002)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.032          -0.049**         0.053   \n                  (0.034)         (0.017)         (0.032)   \nc.neg#c.ri~2        0.008           0.009**        -0.005   \n                  (0.006)         (0.003)         (0.006)   \norder              -0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.018***       -0.038***\n                  (0.003)         (0.004)         (0.004)   \nfemale             -0.005          -0.004           0.005   \n                  (0.004)         (0.003)         (0.005)   \nage                -0.001*          0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.002          -0.003          -0.020   \n                  (0.012)         (0.007)         (0.013)   \nuniversity          0.010          -0.003           0.014** \n                  (0.007)         (0.003)         (0.005)   \n_cons               0.010           0.006          -0.003   \n                  (0.026)         (0.012)         (0.026)   \n------------------------------------------------------------\nr2_w                0.008           0.009           0.011   \nr2_b                0.240           0.004           0.105   \nr2_o                0.009           0.008           0.012   \nN                9747.000        5985.000        8721.000   \nN_g                57.000          35.000          51.000   \n------------------------------------------------------------\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.001          -0.003           0.001   \n                  (0.003)         (0.003)         (0.004)   \ntimesecSto~g       -0.005          -0.016*         -0.010   \n                  (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.001           0.001          -0.000   \n                  (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.013          -0.009           0.035   \n                  (0.016)         (0.018)         (0.030)   \nc.neg#c.ri~2        0.003           0.002          -0.002   \n                  (0.003)         (0.003)         (0.005)   \norder              -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.023***       -0.030***       -0.053***\n                  (0.003)         (0.004)         (0.006)   \nfemale             -0.006*         -0.002           0.004   \n                  (0.002)         (0.004)         (0.006)   \nage                 0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nincome              0.001          -0.011           0.003   \n                  (0.005)         (0.008)         (0.011)   \nuniversity         -0.001           0.004           0.001   \n                  (0.002)         (0.004)         (0.008)   \n_cons               0.019           0.023          -0.021   \n                  (0.014)         (0.018)         (0.031)   \n------------------------------------------------------------\nr2_w                0.008           0.010           0.021   \nr2_b                0.082           0.000           0.009   \nr2_o                0.008           0.010           0.020   \nN               10260.000        8199.000        4104.000   \nN_g                60.000          48.000          24.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.004           0.020***\n                  (0.005)         (0.003)         (0.006)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.015          -0.012           0.020   \n                  (0.036)         (0.028)         (0.047)   \nc.neg#c.ri~2       -0.000           0.004          -0.004   \n                  (0.007)         (0.005)         (0.009)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.003           0.000           0.004   \n                  (0.008)         (0.005)         (0.008)   \nage                 0.005*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.007           0.020           0.014   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.003          -0.003          -0.026*  \n                  (0.022)         (0.007)         (0.012)   \n_cons              -0.111*         -0.016          -0.052   \n                  (0.051)         (0.023)         (0.064)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.021   \nr2_b                0.160           0.184           0.034   \nr2_o                0.010           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.014***        0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.001           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.022           0.022          -0.002   \n                  (0.028)         (0.024)         (0.008)   \nc.neg#c.ri~2       -0.007          -0.001           0.001   \n                  (0.005)         (0.005)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007** \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.003           0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.014           0.011*  \n                  (0.009)         (0.011)         (0.005)   \nuniversity          0.000          -0.004           0.002   \n                  (0.006)         (0.007)         (0.002)   \n_cons              -0.009          -0.006          -0.019*  \n                  (0.023)         (0.025)         (0.008)   \n------------------------------------------------------------\nr2_w                0.029           0.016           0.002   \nr2_b                0.023           0.044           0.193   \nr2_o                0.027           0.016           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.004           0.020** \n                  (0.003)         (0.003)         (0.007)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.014           0.001           0.082   \n                  (0.022)         (0.021)         (0.050)   \nc.neg#c.ri~2        0.006          -0.003          -0.015   \n                  (0.004)         (0.004)         (0.010)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.005           0.006           0.006   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.026           0.007           0.003   \n                  (0.013)         (0.007)         (0.016)   \nuniversity          0.006          -0.005           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.012           0.010          -0.071   \n                  (0.021)         (0.016)         (0.038)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.318           0.152           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n. * Table A4 Row 3 \n.  \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & (negative==1 | negative==0) , r\n> e  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & (negative==1 |\n>  negative==0) , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & (negative==1\n>  | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & (negative==1 |\n>  negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010***        0.014**         0.013   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.013          -0.035           0.055   \n                  (0.008)         (0.033)         (0.055)   \nc.neg#c.ri~2       -0.002           0.000          -0.002   \n                  (0.002)         (0.006)         (0.011)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.028***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.005           0.013   \n                  (0.002)         (0.006)         (0.012)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006          -0.001          -0.048*  \n                  (0.003)         (0.014)         (0.024)   \nuniversity          0.002          -0.001           0.040** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.020*         -0.032          -0.096   \n                  (0.008)         (0.028)         (0.050)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.137           0.023   \nr2_o                0.053           0.011           0.088   \nN              138036.000        5607.000        4617.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.008           0.000   \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.009          -0.032          -0.049** \n                  (0.028)         (0.034)         (0.017)   \nc.neg#c.ri~2       -0.001           0.008           0.009** \n                  (0.005)         (0.006)         (0.003)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.005          -0.005          -0.004   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.002          -0.003   \n                  (0.014)         (0.012)         (0.007)   \nuniversity         -0.003           0.010          -0.003   \n                  (0.005)         (0.007)         (0.003)   \n_cons              -0.003           0.010           0.006   \n                  (0.024)         (0.026)         (0.012)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.009   \nr2_b                0.096           0.240           0.004   \nr2_o                0.011           0.009           0.008   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & (negative==1 |\n>  negative==0) , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & (negative==1\n>  | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & (negative==1\n>  | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & (negative==1 |\n>  negative==0) , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004           0.001          -0.003           0.001   \n                  (0.004)         (0.003)         (0.003)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.053          -0.013          -0.009           0.035   \n                  (0.032)         (0.016)         (0.018)         (0.030)   \nc.neg#c.ri~2       -0.005           0.003           0.002          -0.002   \n                  (0.006)         (0.003)         (0.003)         (0.005)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.053***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.005          -0.006*         -0.002           0.004   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.020           0.001          -0.011           0.003   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.014**        -0.001           0.004           0.001   \n                  (0.005)         (0.002)         (0.004)         (0.008)   \n_cons              -0.003           0.019           0.023          -0.021   \n                  (0.026)         (0.014)         (0.018)         (0.031)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.010           0.021   \nr2_b                0.105           0.082           0.000           0.009   \nr2_o                0.012           0.008           0.010           0.020   \nN                8721.000       10260.000        8199.000        4104.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.004           0.020***\n                  (0.005)         (0.003)         (0.006)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.015          -0.012           0.020   \n                  (0.036)         (0.028)         (0.047)   \nc.neg#c.ri~2       -0.000           0.004          -0.004   \n                  (0.007)         (0.005)         (0.009)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.003           0.000           0.004   \n                  (0.008)         (0.005)         (0.008)   \nage                 0.005*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.007           0.020           0.014   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.003          -0.003          -0.026*  \n                  (0.022)         (0.007)         (0.012)   \n_cons              -0.111*         -0.016          -0.052   \n                  (0.051)         (0.023)         (0.064)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.021   \nr2_b                0.160           0.184           0.034   \nr2_o                0.010           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & (negative==1 |\n>  negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & (negative==1 |\n>  negative==0) , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.014***        0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.001           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.022           0.022          -0.002   \n                  (0.028)         (0.024)         (0.008)   \nc.neg#c.ri~2       -0.007          -0.001           0.001   \n                  (0.005)         (0.005)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007** \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.003           0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.014           0.011*  \n                  (0.009)         (0.011)         (0.005)   \nuniversity          0.000          -0.004           0.002   \n                  (0.006)         (0.007)         (0.002)   \n_cons              -0.009          -0.006          -0.019*  \n                  (0.023)         (0.025)         (0.008)   \n------------------------------------------------------------\nr2_w                0.029           0.016           0.002   \nr2_b                0.023           0.044           0.193   \nr2_o                0.027           0.016           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.004           0.020** \n                  (0.003)         (0.003)         (0.007)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.014           0.001           0.082   \n                  (0.022)         (0.021)         (0.050)   \nc.neg#c.ri~2        0.006          -0.003          -0.015   \n                  (0.004)         (0.004)         (0.010)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.005           0.006           0.006   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.026           0.007           0.003   \n                  (0.013)         (0.007)         (0.016)   \nuniversity          0.006          -0.005           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.012           0.010          -0.071   \n                  (0.021)         (0.016)         (0.038)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.318           0.152           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & (threatening==1 | negative==0) \n> , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & (threatening==\n> 1 | negative==0) , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & (threatening\n> ==1 | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & (threatening==\n> 1 | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011***        0.013*          0.016   \n                  (0.002)         (0.005)         (0.010)   \ntimesecSto~g        0.003           0.026*          0.032   \n                  (0.004)         (0.012)         (0.024)   \nc.neg#c.ti~g       -0.005***       -0.008**        -0.006   \n                  (0.001)         (0.003)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.015          -0.036           0.061   \n                  (0.009)         (0.035)         (0.058)   \nc.neg#c.ri~2       -0.003           0.001          -0.003   \n                  (0.002)         (0.007)         (0.013)   \norder               0.001***        0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.140***       -0.016**        -0.182***\n                  (0.002)         (0.006)         (0.010)   \nfemale              0.001           0.004           0.017   \n                  (0.002)         (0.007)         (0.014)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.004          -0.001          -0.061*  \n                  (0.004)         (0.016)         (0.027)   \nuniversity          0.003           0.001           0.047** \n                  (0.002)         (0.007)         (0.015)   \n_cons              -0.028**        -0.031          -0.104   \n                  (0.009)         (0.031)         (0.054)   \n------------------------------------------------------------\nr2_w                0.060           0.005           0.095   \nr2_b                0.001           0.109           0.007   \nr2_o                0.057           0.006           0.088   \nN              108968.000        4428.000        3645.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g)\n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.008           0.001          -0.001   \n                  (0.005)         (0.005)         (0.002)   \ntimesecSto~g       -0.006           0.002          -0.005   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.003          -0.003           0.000   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.000          -0.025          -0.041*  \n                  (0.030)         (0.034)         (0.016)   \nc.neg#c.ri~2       -0.005           0.009           0.007*  \n                  (0.006)         (0.007)         (0.003)   \norder               0.001          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.020***       -0.028***       -0.016***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.005          -0.010*         -0.002   \n                  (0.006)         (0.005)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.018           0.006          -0.004   \n                  (0.017)         (0.012)         (0.007)   \nuniversity         -0.003           0.006          -0.001   \n                  (0.006)         (0.007)         (0.003)   \n_cons              -0.002           0.028           0.007   \n                  (0.025)         (0.027)         (0.012)   \n------------------------------------------------------------\nr2_w                0.008           0.008           0.006   \nr2_b                0.039           0.227           0.018   \nr2_o                0.008           0.009           0.006   \nN                4860.000        7695.000        4725.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & (threatening==\n> 1 | negative==0) , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & (threatening\n> ==1 | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & (threatening\n> ==1 | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & (threatening==\n> 1 | negative==0) , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.002           0.003           0.001           0.002   \n                  (0.005)         (0.003)         (0.004)         (0.005)   \ntimesecSto~g       -0.016          -0.003          -0.016*         -0.005   \n                  (0.011)         (0.006)         (0.007)         (0.012)   \nc.neg#c.ti~g        0.000          -0.002*          0.001          -0.002   \n                  (0.002)         (0.001)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.024          -0.008           0.008           0.035   \n                  (0.035)         (0.016)         (0.018)         (0.031)   \nc.neg#c.ri~2        0.006           0.001          -0.004           0.005   \n                  (0.007)         (0.004)         (0.004)         (0.006)   \norder               0.000          -0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.042***       -0.022***       -0.037***       -0.043***\n                  (0.005)         (0.004)         (0.004)         (0.007)   \nfemale              0.006          -0.005          -0.002           0.005   \n                  (0.007)         (0.003)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.002*  \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.035          -0.000          -0.009           0.009   \n                  (0.018)         (0.005)         (0.009)         (0.013)   \nuniversity          0.015*         -0.003           0.007           0.003   \n                  (0.007)         (0.003)         (0.005)         (0.009)   \n_cons               0.017           0.014           0.012          -0.060   \n                  (0.028)         (0.015)         (0.019)         (0.034)   \n----------------------------------------------------------------------------\nr2_w                0.013           0.009           0.016           0.018   \nr2_b                0.122           0.039           0.003           0.131   \nr2_o                0.015           0.009           0.015           0.018   \nN                6885.000        8100.000        6480.000        3240.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.005           0.002           0.020** \n                  (0.006)         (0.003)         (0.006)   \ntimesecSto~g        0.003          -0.008           0.004   \n                  (0.013)         (0.008)         (0.014)   \nc.neg#c.ti~g       -0.005          -0.002          -0.010***\n                  (0.003)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.012          -0.007           0.001   \n                  (0.035)         (0.029)         (0.045)   \nc.neg#c.ri~2        0.001           0.003          -0.002   \n                  (0.008)         (0.006)         (0.010)   \norder               0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.027***       -0.045***\n                  (0.006)         (0.005)         (0.005)   \nfemale             -0.003          -0.001          -0.002   \n                  (0.007)         (0.005)         (0.007)   \nage                 0.004*          0.001*          0.001   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.011           0.013           0.000   \n                  (0.018)         (0.013)         (0.014)   \nuniversity         -0.005          -0.003           0.001   \n                  (0.020)         (0.007)         (0.011)   \n_cons              -0.081          -0.010          -0.040   \n                  (0.048)         (0.023)         (0.060)   \n------------------------------------------------------------\nr2_w                0.006           0.009           0.025   \nr2_b                0.183           0.256           0.020   \nr2_o                0.007           0.012           0.024   \nN                4320.000        4995.000        4860.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & (threatening==\n> 1 | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & (threatening==\n> 1 | negative==0) , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.017***        0.002   \n                  (0.005)         (0.005)         (0.002)   \ntimesecSto~g       -0.002           0.013           0.004   \n                  (0.011)         (0.011)         (0.003)   \nc.neg#c.ti~g       -0.006**        -0.009***       -0.002*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.015           0.024           0.000   \n                  (0.028)         (0.025)         (0.009)   \nc.neg#c.ri~2       -0.004          -0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.040***       -0.023***        0.005   \n                  (0.006)         (0.006)         (0.003)   \nfemale             -0.005           0.002           0.002   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.012          -0.007           0.008   \n                  (0.010)         (0.013)         (0.006)   \nuniversity          0.005          -0.005           0.003   \n                  (0.006)         (0.008)         (0.002)   \n_cons              -0.009          -0.017          -0.022** \n                  (0.024)         (0.027)         (0.008)   \n------------------------------------------------------------\nr2_w                0.025           0.014           0.003   \nr2_b                0.000           0.055           0.165   \nr2_o                0.024           0.014           0.005   \nN                4320.000        4320.000        6480.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.006           0.027** \n                  (0.004)         (0.003)         (0.008)   \ntimesecSto~g        0.026**        -0.006           0.022   \n                  (0.010)         (0.008)         (0.018)   \nc.neg#c.ti~g       -0.010***       -0.002          -0.010*  \n                  (0.002)         (0.002)         (0.004)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.012          -0.002           0.085   \n                  (0.022)         (0.021)         (0.054)   \nc.neg#c.ri~2        0.003          -0.001          -0.015   \n                  (0.005)         (0.005)         (0.012)   \norder               0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.012*         -0.043***       -0.316***\n                  (0.006)         (0.004)         (0.006)   \nfemale              0.003           0.002           0.001   \n                  (0.005)         (0.004)         (0.009)   \nage                -0.000          -0.000          -0.001*  \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.009           0.001           0.015   \n                  (0.012)         (0.008)         (0.018)   \nuniversity         -0.002          -0.003           0.013   \n                  (0.005)         (0.005)         (0.009)   \n_cons              -0.037           0.010          -0.096*  \n                  (0.021)         (0.017)         (0.042)   \n------------------------------------------------------------\nr2_w                0.009           0.020           0.146   \nr2_b                0.099           0.061           0.016   \nr2_o                0.009           0.020           0.142   \nN                4158.000        6432.000       18890.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & (disgusting==1 | negative==0) ,\n>  re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & (disgusting==1\n>  | negative==0) , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & (disgusting=\n> =1 | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & (disgusting==1\n>  | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.007***        0.009           0.009   \n                  (0.002)         (0.005)         (0.010)   \ntimesecSto~g       -0.001           0.025*          0.025   \n                  (0.004)         (0.011)         (0.024)   \nc.neg#c.ti~g       -0.003**        -0.007**        -0.003   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.013          -0.048           0.066   \n                  (0.009)         (0.032)         (0.058)   \nc.neg#c.ri~2       -0.002           0.006          -0.006   \n                  (0.002)         (0.007)         (0.013)   \norder               0.000***        0.001**         0.002*  \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.134***       -0.022***       -0.204***\n                  (0.002)         (0.006)         (0.011)   \nfemale              0.001           0.006           0.013   \n                  (0.002)         (0.007)         (0.015)   \nage                -0.000           0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.005          -0.004          -0.026   \n                  (0.004)         (0.015)         (0.028)   \nuniversity          0.001          -0.001           0.038*  \n                  (0.002)         (0.007)         (0.015)   \n_cons              -0.015          -0.055          -0.104   \n                  (0.009)         (0.029)         (0.054)   \n------------------------------------------------------------\nr2_w                0.058           0.008           0.099   \nr2_b                0.041           0.031           0.007   \nr2_o                0.053           0.008           0.094   \nN              101695.000        4131.000        3402.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014**         0.009           0.001   \n                  (0.005)         (0.005)         (0.002)   \ntimesecSto~g        0.002           0.014           0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.002*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.006          -0.036          -0.058***\n                  (0.029)         (0.035)         (0.017)   \nc.neg#c.ri~2       -0.002           0.011           0.012***\n                  (0.006)         (0.008)         (0.003)   \norder               0.000           0.000           0.000** \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.015**        -0.021***       -0.020***\n                  (0.005)         (0.004)         (0.004)   \nfemale              0.004          -0.005          -0.006   \n                  (0.006)         (0.005)         (0.004)   \nage                -0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.004          -0.021           0.001   \n                  (0.016)         (0.013)         (0.008)   \nuniversity         -0.006           0.016*         -0.005   \n                  (0.006)         (0.008)         (0.004)   \n_cons              -0.013           0.005           0.002   \n                  (0.025)         (0.028)         (0.012)   \n------------------------------------------------------------\nr2_w                0.010           0.009           0.013   \nr2_b                0.002           0.125           0.010   \nr2_o                0.010           0.009           0.012   \nN                4536.000        7182.000        4410.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & (disgusting==1\n>  | negative==0) , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & (disgusting=\n> =1 | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & (disgusting=\n> =1 | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & (disgusting==1\n>  | negative==0) , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.005          -0.001          -0.008*         -0.002   \n                  (0.005)         (0.003)         (0.003)         (0.005)   \ntimesecSto~g       -0.018          -0.007          -0.020**        -0.018   \n                  (0.010)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g        0.002          -0.000           0.003*          0.003   \n                  (0.002)         (0.001)         (0.002)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.067*         -0.017          -0.016           0.047   \n                  (0.030)         (0.016)         (0.019)         (0.031)   \nc.neg#c.ri~2       -0.012           0.003           0.006          -0.007   \n                  (0.006)         (0.004)         (0.004)         (0.006)   \norder               0.000          -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.034***       -0.021***       -0.042***       -0.059***\n                  (0.005)         (0.004)         (0.004)         (0.007)   \nfemale              0.002          -0.004          -0.003           0.004   \n                  (0.005)         (0.003)         (0.005)         (0.006)   \nage                 0.000           0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.015           0.003          -0.009           0.009   \n                  (0.013)         (0.006)         (0.011)         (0.013)   \nuniversity          0.013*          0.002           0.004          -0.003   \n                  (0.005)         (0.003)         (0.006)         (0.009)   \n_cons              -0.016           0.019           0.032          -0.018   \n                  (0.024)         (0.015)         (0.020)         (0.034)   \n----------------------------------------------------------------------------\nr2_w                0.010           0.007           0.019           0.027   \nr2_b                0.073           0.012           0.004           0.005   \nr2_o                0.011           0.006           0.018           0.025   \nN                6426.000        7560.000        6039.000        3024.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014*          0.002           0.018*  \n                  (0.006)         (0.003)         (0.007)   \ntimesecSto~g        0.010          -0.006          -0.002   \n                  (0.014)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007*         -0.002          -0.007*  \n                  (0.003)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.027          -0.011           0.023   \n                  (0.039)         (0.030)         (0.048)   \nc.neg#c.ri~2       -0.005           0.004          -0.006   \n                  (0.008)         (0.006)         (0.010)   \norder               0.000           0.001          -0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.021***       -0.052***       -0.034***\n                  (0.006)         (0.006)         (0.005)   \nfemale             -0.010          -0.002           0.000   \n                  (0.009)         (0.006)         (0.008)   \nage                 0.007**         0.000           0.001   \n                  (0.002)         (0.000)         (0.003)   \nincome              0.011           0.023           0.025   \n                  (0.022)         (0.017)         (0.016)   \nuniversity         -0.004           0.000          -0.048***\n                  (0.025)         (0.009)         (0.013)   \n_cons              -0.158**        -0.008          -0.000   \n                  (0.059)         (0.026)         (0.068)   \n------------------------------------------------------------\nr2_w                0.007           0.022           0.017   \nr2_b                0.163           0.002           0.144   \nr2_o                0.009           0.020           0.018   \nN                4032.000        4662.000        4534.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & (disgusting==1\n>  | negative==0) , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & (disgusting==1\n>  | negative==0) , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012**         0.010*         -0.000   \n                  (0.004)         (0.005)         (0.001)   \ntimesecSto~g       -0.005           0.003           0.001   \n                  (0.010)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.005*         -0.005*         -0.000   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.018           0.023          -0.002   \n                  (0.026)         (0.023)         (0.009)   \nc.neg#c.ri~2       -0.006          -0.001           0.001   \n                  (0.006)         (0.005)         (0.002)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.053***       -0.027***        0.015***\n                  (0.006)         (0.006)         (0.003)   \nfemale             -0.003          -0.005           0.000   \n                  (0.006)         (0.005)         (0.002)   \nage                 0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.020*         -0.017           0.014*  \n                  (0.010)         (0.013)         (0.006)   \nuniversity         -0.003          -0.005           0.000   \n                  (0.006)         (0.008)         (0.002)   \n_cons              -0.005           0.011          -0.018*  \n                  (0.022)         (0.025)         (0.008)   \n------------------------------------------------------------\nr2_w                0.031           0.011           0.004   \nr2_b                0.013           0.022           0.173   \nr2_o                0.028           0.011           0.008   \nN                4032.000        4032.000        6048.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009*          0.000           0.015   \n                  (0.004)         (0.003)         (0.008)   \ntimesecSto~g        0.020*         -0.012           0.009   \n                  (0.009)         (0.008)         (0.018)   \nc.neg#c.ti~g       -0.007***        0.001          -0.004   \n                  (0.002)         (0.002)         (0.004)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.020           0.004           0.086   \n                  (0.020)         (0.021)         (0.053)   \nc.neg#c.ri~2        0.008*         -0.004          -0.017   \n                  (0.004)         (0.005)         (0.012)   \norder              -0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.006          -0.027***       -0.309***\n                  (0.006)         (0.004)         (0.006)   \nfemale             -0.001           0.004           0.009   \n                  (0.005)         (0.004)         (0.009)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.025*          0.010           0.014   \n                  (0.012)         (0.009)         (0.019)   \nuniversity          0.006          -0.003           0.004   \n                  (0.005)         (0.006)         (0.009)   \n_cons              -0.007           0.017          -0.079   \n                  (0.019)         (0.017)         (0.041)   \n------------------------------------------------------------\nr2_w                0.005           0.010           0.143   \nr2_b                0.290           0.103           0.016   \nr2_o                0.007           0.011           0.136   \nN                3888.000        6000.000       17631.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   \n. * Table A6 Row 6\n.   replace right2= wp_right2\n(0 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010***        0.014**         0.013   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.013          -0.035           0.055   \n                  (0.008)         (0.033)         (0.055)   \nc.neg#c.ri~2       -0.002           0.000          -0.002   \n                  (0.002)         (0.006)         (0.011)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.028***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.005           0.013   \n                  (0.002)         (0.006)         (0.012)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006          -0.001          -0.048*  \n                  (0.003)         (0.014)         (0.024)   \nuniversity          0.002          -0.001           0.040** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.020*         -0.032          -0.096   \n                  (0.008)         (0.028)         (0.050)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.137           0.023   \nr2_o                0.053           0.011           0.088   \nN              138036.000        5607.000        4617.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.008           0.000   \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.009          -0.032          -0.049** \n                  (0.028)         (0.034)         (0.017)   \nc.neg#c.ri~2       -0.001           0.008           0.009** \n                  (0.005)         (0.006)         (0.003)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.005          -0.005          -0.004   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.002          -0.003   \n                  (0.014)         (0.012)         (0.007)   \nuniversity         -0.003           0.010          -0.003   \n                  (0.005)         (0.007)         (0.003)   \n_cons              -0.003           0.010           0.006   \n                  (0.024)         (0.026)         (0.012)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.009   \nr2_b                0.096           0.240           0.004   \nr2_o                0.011           0.009           0.008   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004           0.001          -0.003           0.001   \n                  (0.004)         (0.003)         (0.003)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.053          -0.013          -0.009           0.035   \n                  (0.032)         (0.016)         (0.018)         (0.030)   \nc.neg#c.ri~2       -0.005           0.003           0.002          -0.002   \n                  (0.006)         (0.003)         (0.003)         (0.005)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.053***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.005          -0.006*         -0.002           0.004   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.020           0.001          -0.011           0.003   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.014**        -0.001           0.004           0.001   \n                  (0.005)         (0.002)         (0.004)         (0.008)   \n_cons              -0.003           0.019           0.023          -0.021   \n                  (0.026)         (0.014)         (0.018)         (0.031)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.010           0.021   \nr2_b                0.105           0.082           0.000           0.009   \nr2_o                0.012           0.008           0.010           0.020   \nN                8721.000       10260.000        8199.000        4104.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.004           0.020***\n                  (0.005)         (0.003)         (0.006)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.015          -0.012           0.020   \n                  (0.036)         (0.028)         (0.047)   \nc.neg#c.ri~2       -0.000           0.004          -0.004   \n                  (0.007)         (0.005)         (0.009)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.003           0.000           0.004   \n                  (0.008)         (0.005)         (0.008)   \nage                 0.005*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.007           0.020           0.014   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.003          -0.003          -0.026*  \n                  (0.022)         (0.007)         (0.012)   \n_cons              -0.111*         -0.016          -0.052   \n                  (0.051)         (0.023)         (0.064)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.021   \nr2_b                0.160           0.184           0.034   \nr2_o                0.010           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.014***        0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.001           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.022           0.022          -0.002   \n                  (0.028)         (0.024)         (0.008)   \nc.neg#c.ri~2       -0.007          -0.001           0.001   \n                  (0.005)         (0.005)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007** \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.003           0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.014           0.011*  \n                  (0.009)         (0.011)         (0.005)   \nuniversity          0.000          -0.004           0.002   \n                  (0.006)         (0.007)         (0.002)   \n_cons              -0.009          -0.006          -0.019*  \n                  (0.023)         (0.025)         (0.008)   \n------------------------------------------------------------\nr2_w                0.029           0.016           0.002   \nr2_b                0.023           0.044           0.193   \nr2_o                0.027           0.016           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.004           0.020** \n                  (0.003)         (0.003)         (0.007)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.014           0.001           0.082   \n                  (0.022)         (0.021)         (0.050)   \nc.neg#c.ri~2        0.006          -0.003          -0.015   \n                  (0.004)         (0.004)         (0.010)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.005           0.006           0.006   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.026           0.007           0.003   \n                  (0.013)         (0.007)         (0.016)   \nuniversity          0.006          -0.005           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.012           0.010          -0.071   \n                  (0.021)         (0.016)         (0.038)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.318           0.152           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   replace right2= wp_right2_dicho2\n(430,722 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.014***        0.013   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.030   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.010**         0.000           0.040   \n                  (0.004)         (0.013)         (0.030)   \nc.neg#c.ri~2       -0.002*         -0.002          -0.001   \n                  (0.001)         (0.002)         (0.006)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.028***       -0.187***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.004           0.011   \n                  (0.002)         (0.007)         (0.012)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006          -0.002          -0.037   \n                  (0.003)         (0.015)         (0.024)   \nuniversity          0.002          -0.003           0.037** \n                  (0.002)         (0.007)         (0.013)   \n_cons              -0.019*         -0.044          -0.088   \n                  (0.007)         (0.027)         (0.048)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.005           0.049           0.069   \nr2_o                0.053           0.010           0.089   \nN              138036.000        5607.000        4617.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010**         0.011**         0.002   \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.007          -0.004          -0.022** \n                  (0.014)         (0.010)         (0.007)   \nc.neg#c.ri~2       -0.002           0.002           0.004***\n                  (0.003)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.004          -0.005          -0.004   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.011          -0.004          -0.003   \n                  (0.014)         (0.012)         (0.007)   \nuniversity         -0.002           0.009          -0.003   \n                  (0.005)         (0.006)         (0.003)   \n_cons              -0.010          -0.002          -0.004   \n                  (0.021)         (0.022)         (0.011)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.009   \nr2_b                0.052           0.269           0.003   \nr2_o                0.011           0.009           0.008   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003           0.002          -0.001           0.001   \n                  (0.004)         (0.002)         (0.003)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.025          -0.008           0.004           0.014   \n                  (0.015)         (0.009)         (0.008)         (0.014)   \nc.neg#c.ri~2       -0.005           0.001          -0.001          -0.001   \n                  (0.003)         (0.002)         (0.002)         (0.003)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.052***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.006          -0.006*         -0.002           0.005   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                 0.000           0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.024           0.001          -0.010          -0.000   \n                  (0.014)         (0.005)         (0.008)         (0.011)   \nuniversity          0.015**        -0.000           0.005          -0.000   \n                  (0.005)         (0.003)         (0.004)         (0.008)   \n_cons               0.006           0.018           0.015          -0.003   \n                  (0.024)         (0.013)         (0.015)         (0.027)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.010           0.021   \nr2_b                0.057           0.092           0.001           0.007   \nr2_o                0.011           0.008           0.010           0.020   \nN                8721.000       10260.000        8199.000        4104.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011*          0.005           0.018***\n                  (0.004)         (0.003)         (0.005)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.017          -0.012          -0.002   \n                  (0.016)         (0.018)         (0.019)   \nc.neg#c.ri~2       -0.002           0.003           0.002   \n                  (0.003)         (0.003)         (0.004)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.002           0.000           0.005   \n                  (0.008)         (0.005)         (0.007)   \nage                 0.005*          0.001           0.003   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.007           0.020           0.015   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.007          -0.002          -0.028*  \n                  (0.022)         (0.008)         (0.012)   \n_cons              -0.112*         -0.018          -0.055   \n                  (0.048)         (0.022)         (0.057)   \n------------------------------------------------------------\nr2_w                0.009           0.015           0.021   \nr2_b                0.184           0.179           0.042   \nr2_o                0.011           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.015***        0.014***        0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.000           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.009           0.007          -0.003   \n                  (0.013)         (0.012)         (0.003)   \nc.neg#c.ri~2       -0.001           0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007** \n                  (0.005)         (0.005)         (0.003)   \nfemale              0.000           0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.012          -0.016           0.012*  \n                  (0.009)         (0.012)         (0.005)   \nuniversity         -0.002          -0.003           0.002   \n                  (0.006)         (0.007)         (0.002)   \n_cons              -0.005           0.000          -0.018** \n                  (0.021)         (0.023)         (0.007)   \n------------------------------------------------------------\nr2_w                0.028           0.016           0.003   \nr2_b                0.011           0.026           0.192   \nr2_o                0.026           0.016           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***        0.003           0.018** \n                  (0.003)         (0.003)         (0.006)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.012           0.012           0.060** \n                  (0.011)         (0.010)         (0.021)   \nc.neg#c.ri~2        0.004          -0.002          -0.012** \n                  (0.002)         (0.002)         (0.004)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.302***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.004           0.006           0.005   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000*         -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.023           0.005           0.004   \n                  (0.014)         (0.007)         (0.016)   \nuniversity          0.005          -0.006           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.017           0.011          -0.056   \n                  (0.020)         (0.015)         (0.035)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.281           0.133           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   replace right2= wp_right2_dichox\n(122,898 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.013**         0.012   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.001          -0.020          -0.002   \n                  (0.004)         (0.012)         (0.024)   \nc.neg#c.ri~2       -0.001           0.001           0.003   \n                  (0.001)         (0.002)         (0.005)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.028***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.003           0.011   \n                  (0.002)         (0.006)         (0.013)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006           0.002          -0.048*  \n                  (0.003)         (0.013)         (0.024)   \nuniversity          0.002           0.000           0.040** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.016*         -0.033          -0.081   \n                  (0.007)         (0.026)         (0.050)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.234           0.003   \nr2_o                0.053           0.012           0.088   \nN              138036.000        5607.000        4617.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010**         0.012***        0.002   \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.002          -0.003          -0.010   \n                  (0.011)         (0.009)         (0.006)   \nc.neg#c.ri~2       -0.001           0.001           0.002   \n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.022***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.004          -0.005          -0.005   \n                  (0.005)         (0.005)         (0.004)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.019          -0.002          -0.003   \n                  (0.014)         (0.012)         (0.007)   \nuniversity         -0.001           0.010          -0.003   \n                  (0.005)         (0.006)         (0.003)   \n_cons              -0.006          -0.006          -0.003   \n                  (0.022)         (0.022)         (0.012)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.007   \nr2_b                0.159           0.237           0.003   \nr2_o                0.011           0.009           0.007   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003           0.002          -0.002           0.002   \n                  (0.004)         (0.002)         (0.002)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.014          -0.004           0.001           0.023   \n                  (0.011)         (0.006)         (0.007)         (0.012)   \nc.neg#c.ri~2       -0.001           0.001          -0.000          -0.002   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.037***       -0.023***       -0.030***       -0.053***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.006          -0.006*         -0.002           0.000   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.024           0.001          -0.010           0.002   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.013*         -0.001           0.004           0.001   \n                  (0.005)         (0.002)         (0.004)         (0.008)   \n_cons               0.008           0.014           0.017          -0.021   \n                  (0.024)         (0.011)         (0.015)         (0.028)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.010           0.021   \nr2_b                0.092           0.092           0.000           0.045   \nr2_o                0.011           0.008           0.010           0.021   \nN                8721.000       10260.000        8199.000        4104.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.005           0.018***\n                  (0.005)         (0.003)         (0.005)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.014           0.002           0.001   \n                  (0.014)         (0.008)         (0.016)   \nc.neg#c.ri~2       -0.000           0.001          -0.001   \n                  (0.003)         (0.002)         (0.003)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.023***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale              0.001           0.001           0.003   \n                  (0.008)         (0.005)         (0.008)   \nage                 0.005*          0.001*          0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.007           0.019           0.013   \n                  (0.018)         (0.013)         (0.015)   \nuniversity          0.003          -0.002          -0.025*  \n                  (0.021)         (0.007)         (0.012)   \n_cons              -0.129**        -0.024          -0.036   \n                  (0.049)         (0.022)         (0.059)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.021   \nr2_b                0.231           0.241           0.037   \nr2_o                0.011           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***        0.014***        0.002   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.001           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.006           0.003          -0.002   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ri~2       -0.000          -0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007** \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.004           0.003           0.001   \n                  (0.005)         (0.004)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.013           0.012*  \n                  (0.009)         (0.012)         (0.005)   \nuniversity          0.001          -0.005           0.001   \n                  (0.006)         (0.007)         (0.002)   \n_cons               0.000           0.001          -0.019** \n                  (0.022)         (0.022)         (0.006)   \n------------------------------------------------------------\nr2_w                0.028           0.016           0.002   \nr2_b                0.003           0.000           0.183   \nr2_o                0.027           0.015           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***        0.003           0.017** \n                  (0.003)         (0.003)         (0.006)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.002          -0.006           0.018   \n                  (0.010)         (0.008)         (0.018)   \nc.neg#c.ri~2        0.001           0.000          -0.004   \n                  (0.002)         (0.001)         (0.003)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.034***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.004           0.006           0.005   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.029*          0.008           0.005   \n                  (0.014)         (0.007)         (0.016)   \nuniversity          0.008          -0.006           0.005   \n                  (0.006)         (0.005)         (0.008)   \n_cons              -0.017           0.013          -0.051   \n                  (0.020)         (0.016)         (0.035)   \n------------------------------------------------------------\nr2_w                0.007           0.014           0.139   \nr2_b                0.328           0.160           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   replace right2= left_right2\n(418,383 real changes made, 561 to missing)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.012**         0.014   \n                  (0.001)         (0.004)         (0.009)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.006          -0.042           0.036   \n                  (0.007)         (0.023)         (0.046)   \nc.neg#c.ri~2       -0.001           0.004          -0.003   \n                  (0.001)         (0.004)         (0.009)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.027***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.004           0.008   \n                  (0.002)         (0.006)         (0.012)   \nage                -0.000          -0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006           0.003          -0.049*  \n                  (0.003)         (0.014)         (0.024)   \nuniversity          0.002          -0.001           0.041** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.018*         -0.018          -0.099   \n                  (0.008)         (0.028)         (0.052)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.148           0.011   \nr2_o                0.053           0.011           0.088   \nN              137865.000        5607.000        4617.000   \nN_g               807.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009*          0.008           0.000   \n                  (0.004)         (0.005)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003          -0.026          -0.034** \n                  (0.024)         (0.028)         (0.013)   \nc.neg#c.ri~2        0.001           0.006           0.006** \n                  (0.005)         (0.005)         (0.002)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.003          -0.004          -0.004   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.010          -0.001          -0.001   \n                  (0.014)         (0.011)         (0.008)   \nuniversity         -0.001           0.010          -0.003   \n                  (0.005)         (0.007)         (0.003)   \n_cons              -0.008           0.011           0.007   \n                  (0.023)         (0.029)         (0.013)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.008   \nr2_b                0.050           0.236           0.007   \nr2_o                0.011           0.009           0.007   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.002           0.003          -0.004           0.004   \n                  (0.004)         (0.002)         (0.003)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.025          -0.000          -0.018           0.015   \n                  (0.024)         (0.012)         (0.013)         (0.020)   \nc.neg#c.ri~2        0.001          -0.001           0.004          -0.006   \n                  (0.005)         (0.002)         (0.002)         (0.004)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.051***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.004          -0.006**        -0.002           0.002   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.022           0.002          -0.010          -0.002   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.017**        -0.002           0.004           0.000   \n                  (0.005)         (0.003)         (0.004)         (0.008)   \n_cons              -0.000           0.010           0.027          -0.000   \n                  (0.026)         (0.013)         (0.016)         (0.027)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.011           0.021   \nr2_b                0.139           0.098           0.001           0.000   \nr2_o                0.012           0.008           0.010           0.020   \nN                8721.000       10089.000        8199.000        4104.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013*          0.005           0.013   \n                  (0.006)         (0.003)         (0.007)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.016           0.005          -0.044   \n                  (0.031)         (0.019)         (0.050)   \nc.neg#c.ri~2       -0.004           0.001           0.012   \n                  (0.006)         (0.003)         (0.010)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.002           0.001           0.004   \n                  (0.008)         (0.005)         (0.007)   \nage                 0.004*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.004           0.019           0.014   \n                  (0.019)         (0.013)         (0.014)   \nuniversity         -0.003          -0.002          -0.026*  \n                  (0.022)         (0.007)         (0.012)   \n_cons              -0.113*         -0.020          -0.029   \n                  (0.052)         (0.023)         (0.061)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.022   \nr2_b                0.145           0.193           0.036   \nr2_o                0.010           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.015***        0.014**         0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.000           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.006           0.019          -0.010*  \n                  (0.027)         (0.031)         (0.004)   \nc.neg#c.ri~2       -0.001           0.000           0.002** \n                  (0.005)         (0.006)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007*  \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.001           0.001           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.013          -0.010           0.013*  \n                  (0.009)         (0.012)         (0.005)   \nuniversity         -0.001          -0.003           0.001   \n                  (0.005)         (0.007)         (0.002)   \n_cons              -0.005          -0.003          -0.016*  \n                  (0.024)         (0.025)         (0.006)   \n------------------------------------------------------------\nr2_w                0.028           0.016           0.003   \nr2_b                0.021           0.028           0.183   \nr2_o                0.026           0.016           0.006   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.004           0.019** \n                  (0.004)         (0.003)         (0.007)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.008           0.002           0.041   \n                  (0.021)         (0.021)         (0.036)   \nc.neg#c.ri~2        0.004          -0.002          -0.010   \n                  (0.004)         (0.004)         (0.007)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.003           0.005           0.005   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000*         -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.031*          0.007           0.005   \n                  (0.015)         (0.007)         (0.016)   \nuniversity          0.005          -0.006           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.011           0.012          -0.060   \n                  (0.022)         (0.017)         (0.037)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.292           0.145           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   replace right2= left_right2_dichox\n(397,743 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.008***        0.013**         0.013   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003          -0.022          -0.005   \n                  (0.004)         (0.012)         (0.024)   \nc.neg#c.ri~2        0.001           0.001           0.000   \n                  (0.001)         (0.002)         (0.005)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.027***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.005           0.007   \n                  (0.002)         (0.006)         (0.012)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006          -0.002          -0.046   \n                  (0.003)         (0.012)         (0.024)   \nuniversity          0.002          -0.002           0.039** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.014          -0.027          -0.079   \n                  (0.008)         (0.026)         (0.050)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.212           0.000   \nr2_o                0.053           0.011           0.087   \nN              137865.000        5607.000        4617.000   \nN_g               807.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010**         0.012***        0.002   \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.001          -0.002          -0.009   \n                  (0.011)         (0.009)         (0.006)   \nc.neg#c.ri~2       -0.000           0.000           0.001   \n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.004          -0.004          -0.004   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.011          -0.001          -0.002   \n                  (0.014)         (0.011)         (0.007)   \nuniversity         -0.001           0.010          -0.004   \n                  (0.005)         (0.006)         (0.003)   \n_cons              -0.009          -0.006          -0.004   \n                  (0.022)         (0.022)         (0.011)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.007   \nr2_b                0.049           0.237           0.009   \nr2_o                0.011           0.009           0.007   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003           0.002          -0.003           0.003   \n                  (0.004)         (0.002)         (0.002)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.011          -0.005          -0.011           0.010   \n                  (0.011)         (0.006)         (0.007)         (0.011)   \nc.neg#c.ri~2       -0.000           0.000           0.002          -0.004   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.051***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.005          -0.007**        -0.002           0.003   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                 0.000           0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.022           0.002          -0.011          -0.001   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.016**        -0.002           0.004           0.002   \n                  (0.005)         (0.003)         (0.004)         (0.008)   \n_cons               0.006           0.013           0.023          -0.001   \n                  (0.024)         (0.011)         (0.015)         (0.025)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.011           0.022   \nr2_b                0.094           0.108           0.001           0.005   \nr2_o                0.011           0.009           0.010           0.021   \nN                8721.000       10089.000        8199.000        4104.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.005*          0.015** \n                  (0.004)         (0.003)         (0.005)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.004           0.005          -0.022   \n                  (0.014)         (0.008)         (0.015)   \nc.neg#c.ri~2       -0.000          -0.000           0.006*  \n                  (0.003)         (0.002)         (0.003)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.040***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.003           0.001           0.002   \n                  (0.008)         (0.005)         (0.008)   \nage                 0.004*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.003           0.019           0.014   \n                  (0.019)         (0.013)         (0.014)   \nuniversity         -0.001          -0.001          -0.027*  \n                  (0.022)         (0.008)         (0.012)   \n_cons              -0.097*         -0.023          -0.035   \n                  (0.048)         (0.023)         (0.055)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.022   \nr2_b                0.164           0.193           0.044   \nr2_o                0.010           0.016           0.022   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***        0.012**         0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.000           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.008          -0.006          -0.010***\n                  (0.011)         (0.012)         (0.003)   \nc.neg#c.ri~2        0.001           0.002           0.002***\n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.024***        0.006*  \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.004           0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.012          -0.012           0.013*  \n                  (0.009)         (0.012)         (0.005)   \nuniversity         -0.001          -0.004           0.001   \n                  (0.005)         (0.007)         (0.002)   \n_cons               0.003           0.008          -0.015*  \n                  (0.022)         (0.023)         (0.006)   \n------------------------------------------------------------\nr2_w                0.028           0.016           0.004   \nr2_b                0.008           0.002           0.185   \nr2_o                0.027           0.015           0.006   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.003           0.015*  \n                  (0.003)         (0.003)         (0.006)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003          -0.004          -0.000   \n                  (0.010)         (0.008)         (0.018)   \nc.neg#c.ri~2        0.003          -0.000           0.000   \n                  (0.002)         (0.001)         (0.003)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.004           0.004           0.005   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000*         -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.032*          0.008           0.004   \n                  (0.014)         (0.007)         (0.016)   \nuniversity          0.006          -0.007           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.013           0.016          -0.043   \n                  (0.020)         (0.016)         (0.036)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.350           0.186           0.000   \nr2_o                0.011           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   replace right2= ideo_right2\n(444,626 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010***        0.012**         0.014   \n                  (0.001)         (0.005)         (0.009)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.013          -0.052           0.048   \n                  (0.009)         (0.030)         (0.053)   \nc.neg#c.ri~2       -0.002           0.003          -0.003   \n                  (0.002)         (0.006)         (0.010)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.027***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.005           0.010   \n                  (0.002)         (0.006)         (0.012)   \nage                -0.000          -0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006           0.003          -0.049*  \n                  (0.003)         (0.013)         (0.024)   \nuniversity          0.002          -0.000           0.041** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.021*         -0.020          -0.100   \n                  (0.008)         (0.028)         (0.051)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.182           0.018   \nr2_o                0.053           0.011           0.088   \nN              137865.000        5607.000        4617.000   \nN_g               807.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.005          -0.000   \n                  (0.004)         (0.006)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.007          -0.050          -0.046** \n                  (0.030)         (0.041)         (0.016)   \nc.neg#c.ri~2        0.000           0.012           0.008** \n                  (0.006)         (0.008)         (0.003)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.005          -0.004          -0.005   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.012          -0.002          -0.002   \n                  (0.014)         (0.012)         (0.008)   \nuniversity         -0.002           0.010          -0.003   \n                  (0.005)         (0.007)         (0.003)   \n_cons              -0.006           0.023           0.009   \n                  (0.024)         (0.031)         (0.013)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.009   \nr2_b                0.057           0.237           0.007   \nr2_o                0.011           0.009           0.008   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003           0.003          -0.006           0.005   \n                  (0.004)         (0.003)         (0.003)         (0.005)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.042          -0.012          -0.028           0.036   \n                  (0.030)         (0.023)         (0.021)         (0.033)   \nc.neg#c.ri~2       -0.002           0.000           0.007          -0.008   \n                  (0.006)         (0.004)         (0.004)         (0.006)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.052***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.005          -0.006**        -0.002           0.003   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.021           0.002          -0.010          -0.003   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.016**        -0.002           0.005          -0.001   \n                  (0.005)         (0.003)         (0.004)         (0.008)   \n_cons              -0.004           0.017           0.034          -0.005   \n                  (0.026)         (0.018)         (0.019)         (0.030)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.011           0.021   \nr2_b                0.134           0.098           0.001           0.030   \nr2_o                0.012           0.008           0.010           0.020   \nN                8721.000       10089.000        8199.000        4104.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.020*          0.005           0.016*  \n                  (0.010)         (0.003)         (0.007)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.111          -0.000          -0.013   \n                  (0.088)         (0.024)         (0.058)   \nc.neg#c.ri~2       -0.018           0.002           0.004   \n                  (0.016)         (0.005)         (0.011)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.001           0.001           0.004   \n                  (0.008)         (0.005)         (0.007)   \nage                 0.004*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.006           0.019           0.015   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.006          -0.002          -0.026*  \n                  (0.022)         (0.007)         (0.012)   \n_cons              -0.160*         -0.018          -0.045   \n                  (0.068)         (0.023)         (0.066)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.021   \nr2_b                0.154           0.191           0.035   \nr2_o                0.011           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.014**         0.000   \n                  (0.004)         (0.005)         (0.001)   \ntimesecSto~g       -0.000           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.016           0.036          -0.015*  \n                  (0.030)         (0.035)         (0.007)   \nc.neg#c.ri~2       -0.005          -0.001           0.003** \n                  (0.006)         (0.007)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007*  \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.002           0.000           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.013          -0.011           0.012*  \n                  (0.009)         (0.011)         (0.005)   \nuniversity         -0.000          -0.003           0.001   \n                  (0.006)         (0.007)         (0.002)   \n_cons              -0.008          -0.010          -0.012   \n                  (0.024)         (0.027)         (0.007)   \n------------------------------------------------------------\nr2_w                0.028           0.016           0.003   \nr2_b                0.021           0.083           0.182   \nr2_o                0.027           0.016           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012***        0.004           0.020** \n                  (0.004)         (0.003)         (0.007)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.013           0.002           0.065   \n                  (0.023)         (0.023)         (0.045)   \nc.neg#c.ri~2        0.006          -0.003          -0.014   \n                  (0.004)         (0.004)         (0.009)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.004           0.005           0.005   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.029*          0.008           0.004   \n                  (0.014)         (0.007)         (0.016)   \nuniversity          0.006          -0.005           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.010           0.011          -0.067   \n                  (0.021)         (0.017)         (0.038)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.311           0.153           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   replace right2= ideo_right2_dichox\n(444,626 real changes made)\n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.013**         0.013   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.002          -0.023*         -0.002   \n                  (0.004)         (0.012)         (0.023)   \nc.neg#c.ri~2       -0.000           0.002          -0.001   \n                  (0.001)         (0.002)         (0.005)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.027***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.006           0.006   \n                  (0.002)         (0.005)         (0.012)   \nage                -0.000          -0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006          -0.006          -0.047   \n                  (0.003)         (0.012)         (0.024)   \nuniversity          0.002           0.001           0.040** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.016*         -0.026          -0.083   \n                  (0.008)         (0.026)         (0.050)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.225           0.000   \nr2_o                0.053           0.012           0.087   \nN              137865.000        5607.000        4617.000   \nN_g               807.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010**         0.011***        0.003   \n                  (0.004)         (0.003)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.000          -0.006          -0.009   \n                  (0.011)         (0.009)         (0.006)   \nc.neg#c.ri~2       -0.000           0.002           0.001   \n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.004          -0.005          -0.005   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.012          -0.004          -0.002   \n                  (0.015)         (0.012)         (0.008)   \nuniversity         -0.001           0.010          -0.003   \n                  (0.005)         (0.006)         (0.003)   \n_cons              -0.009          -0.005          -0.005   \n                  (0.022)         (0.022)         (0.012)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.007   \nr2_b                0.051           0.266           0.010   \nr2_o                0.011           0.009           0.007   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.003           0.003          -0.003           0.002   \n                  (0.004)         (0.002)         (0.002)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.014          -0.002          -0.010           0.009   \n                  (0.011)         (0.005)         (0.007)         (0.012)   \nc.neg#c.ri~2       -0.001          -0.000           0.002          -0.002   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.052***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.005          -0.006**        -0.002           0.004   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                 0.000           0.000           0.000           0.000   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.021           0.001          -0.010          -0.003   \n                  (0.013)         (0.005)         (0.009)         (0.011)   \nuniversity          0.015**        -0.001           0.005          -0.000   \n                  (0.005)         (0.002)         (0.004)         (0.008)   \n_cons               0.005           0.011           0.023           0.003   \n                  (0.024)         (0.011)         (0.015)         (0.027)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.011           0.021   \nr2_b                0.091           0.110           0.001           0.036   \nr2_o                0.011           0.009           0.010           0.020   \nN                8721.000       10089.000        8199.000        4104.000   \nN_g                51.000          59.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013**         0.006*          0.016** \n                  (0.005)         (0.003)         (0.005)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.023           0.006          -0.015   \n                  (0.014)         (0.008)         (0.015)   \nc.neg#c.ri~2       -0.005          -0.000           0.004   \n                  (0.003)         (0.002)         (0.003)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.002           0.001           0.004   \n                  (0.008)         (0.005)         (0.007)   \nage                 0.004*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.004           0.020           0.015   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.004          -0.001          -0.026*  \n                  (0.022)         (0.008)         (0.012)   \n_cons              -0.111*         -0.024          -0.043   \n                  (0.049)         (0.023)         (0.057)   \n------------------------------------------------------------\nr2_w                0.010           0.014           0.022   \nr2_b                0.143           0.194           0.037   \nr2_o                0.011           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014***        0.014***        0.002   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.000           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003           0.005          -0.005   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ri~2        0.001          -0.001           0.001   \n                  (0.002)         (0.002)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007*  \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.001           0.003           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.013          -0.013           0.013*  \n                  (0.009)         (0.012)         (0.005)   \nuniversity         -0.001          -0.004           0.001   \n                  (0.005)         (0.007)         (0.002)   \n_cons              -0.001           0.001          -0.018** \n                  (0.022)         (0.022)         (0.006)   \n------------------------------------------------------------\nr2_w                0.028           0.016           0.003   \nr2_b                0.020           0.000           0.183   \nr2_o                0.026           0.015           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.003           0.016*  \n                  (0.003)         (0.003)         (0.006)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.003          -0.002           0.008   \n                  (0.010)         (0.008)         (0.018)   \nc.neg#c.ri~2        0.003          -0.001          -0.001   \n                  (0.002)         (0.001)         (0.003)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.004           0.005           0.005   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.032*          0.008           0.004   \n                  (0.014)         (0.007)         (0.016)   \nuniversity          0.006          -0.006           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.013           0.013          -0.047   \n                  (0.020)         (0.016)         (0.035)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.350           0.194           0.000   \nr2_o                0.011           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n. * Table A8 Row 6\n.   replace right2= wp_right2\n(431,283 real changes made)\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & wp_right2_ext==1, re   \n.   estimates store B \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & political_interest_dichox==1, r\n> e   \n.   estimates store C\n.   esttab  A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010***        0.009***        0.012***\n                  (0.001)         (0.002)         (0.002)   \ntimesecSto~g        0.002           0.004           0.012*  \n                  (0.004)         (0.005)         (0.005)   \nc.neg#c.ti~g       -0.004***       -0.004***       -0.006***\n                  (0.001)         (0.001)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.013           0.007           0.014   \n                  (0.008)         (0.009)         (0.011)   \nc.neg#c.ri~2       -0.002          -0.001          -0.002   \n                  (0.002)         (0.002)         (0.002)   \norder               0.000*          0.000*          0.000** \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.131***       -0.129***       -0.132***\n                  (0.002)         (0.002)         (0.002)   \nfemale              0.003           0.001           0.003   \n                  (0.002)         (0.002)         (0.002)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.006          -0.005          -0.009   \n                  (0.003)         (0.004)         (0.005)   \nuniversity          0.002           0.003           0.005   \n                  (0.002)         (0.002)         (0.003)   \n_cons              -0.020*         -0.019          -0.039***\n                  (0.008)         (0.010)         (0.012)   \n------------------------------------------------------------\nr2_w                0.055           0.054           0.057   \nr2_b                0.006           0.029           0.017   \nr2_o                0.053           0.052           0.054   \nN              138036.000       74334.000       64760.000   \nN_g               808.000         435.000         379.000   \n------------------------------------------------------------\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 , re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 , re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010***        0.014**         0.013   \n                  (0.001)         (0.004)         (0.008)   \ntimesecSto~g        0.002           0.026*          0.031   \n                  (0.004)         (0.011)         (0.023)   \nc.neg#c.ti~g       -0.004***       -0.009***       -0.006   \n                  (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.013          -0.035           0.055   \n                  (0.008)         (0.033)         (0.055)   \nc.neg#c.ri~2       -0.002           0.000          -0.002   \n                  (0.002)         (0.006)         (0.011)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.131***       -0.028***       -0.186***\n                  (0.002)         (0.005)         (0.009)   \nfemale              0.003           0.005           0.013   \n                  (0.002)         (0.006)         (0.012)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.006          -0.001          -0.048*  \n                  (0.003)         (0.014)         (0.024)   \nuniversity          0.002          -0.001           0.040** \n                  (0.002)         (0.006)         (0.013)   \n_cons              -0.020*         -0.032          -0.096   \n                  (0.008)         (0.028)         (0.050)   \n------------------------------------------------------------\nr2_w                0.055           0.010           0.092   \nr2_b                0.006           0.137           0.023   \nr2_o                0.053           0.011           0.088   \nN              138036.000        5607.000        4617.000   \nN_g               808.000          33.000          27.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.008           0.000   \n                  (0.004)         (0.004)         (0.002)   \ntimesecSto~g       -0.001           0.011          -0.001   \n                  (0.011)         (0.009)         (0.005)   \nc.neg#c.ti~g       -0.005**        -0.006***       -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.009          -0.032          -0.049** \n                  (0.028)         (0.034)         (0.017)   \nc.neg#c.ri~2       -0.001           0.008           0.009** \n                  (0.005)         (0.006)         (0.003)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.021***       -0.021***       -0.018***\n                  (0.004)         (0.003)         (0.004)   \nfemale              0.005          -0.005          -0.004   \n                  (0.005)         (0.004)         (0.003)   \nage                 0.000          -0.001*          0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.002          -0.003   \n                  (0.014)         (0.012)         (0.007)   \nuniversity         -0.003           0.010          -0.003   \n                  (0.005)         (0.007)         (0.003)   \n_cons              -0.003           0.010           0.006   \n                  (0.024)         (0.026)         (0.012)   \n------------------------------------------------------------\nr2_w                0.011           0.008           0.009   \nr2_b                0.096           0.240           0.004   \nr2_o                0.011           0.009           0.008   \nN                6156.000        9747.000        5985.000   \nN_g                36.000          57.000          35.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 , re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 , re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.004           0.001          -0.003           0.001   \n                  (0.004)         (0.003)         (0.003)         (0.004)   \ntimesecSto~g       -0.015          -0.005          -0.016*         -0.010   \n                  (0.011)         (0.005)         (0.007)         (0.011)   \nc.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   \n                  (0.002)         (0.001)         (0.001)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.053          -0.013          -0.009           0.035   \n                  (0.032)         (0.016)         (0.018)         (0.030)   \nc.neg#c.ri~2       -0.005           0.003           0.002          -0.002   \n                  (0.006)         (0.003)         (0.003)         (0.005)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.038***       -0.023***       -0.030***       -0.053***\n                  (0.004)         (0.003)         (0.004)         (0.006)   \nfemale              0.005          -0.006*         -0.002           0.004   \n                  (0.005)         (0.002)         (0.004)         (0.006)   \nage                -0.000           0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.000)         (0.001)   \nincome             -0.020           0.001          -0.011           0.003   \n                  (0.013)         (0.005)         (0.008)         (0.011)   \nuniversity          0.014**        -0.001           0.004           0.001   \n                  (0.005)         (0.002)         (0.004)         (0.008)   \n_cons              -0.003           0.019           0.023          -0.021   \n                  (0.026)         (0.014)         (0.018)         (0.031)   \n----------------------------------------------------------------------------\nr2_w                0.011           0.008           0.010           0.021   \nr2_b                0.105           0.082           0.000           0.009   \nr2_o                0.012           0.008           0.010           0.020   \nN                8721.000       10260.000        8199.000        4104.000   \nN_g                51.000          60.000          48.000          24.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.004           0.020***\n                  (0.005)         (0.003)         (0.006)   \ntimesecSto~g        0.009          -0.004           0.001   \n                  (0.013)         (0.008)         (0.015)   \nc.neg#c.ti~g       -0.007**        -0.004*         -0.009** \n                  (0.002)         (0.002)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.015          -0.012           0.020   \n                  (0.036)         (0.028)         (0.047)   \nc.neg#c.ri~2       -0.000           0.004          -0.004   \n                  (0.007)         (0.005)         (0.009)   \norder               0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.024***       -0.033***       -0.039***\n                  (0.005)         (0.005)         (0.004)   \nfemale             -0.003           0.000           0.004   \n                  (0.008)         (0.005)         (0.008)   \nage                 0.005*          0.001           0.002   \n                  (0.002)         (0.000)         (0.002)   \nincome              0.007           0.020           0.014   \n                  (0.019)         (0.013)         (0.015)   \nuniversity         -0.003          -0.003          -0.026*  \n                  (0.022)         (0.007)         (0.012)   \n_cons              -0.111*         -0.016          -0.052   \n                  (0.051)         (0.023)         (0.064)   \n------------------------------------------------------------\nr2_w                0.009           0.014           0.021   \nr2_b                0.160           0.184           0.034   \nr2_o                0.010           0.016           0.021   \nN                5472.000        6327.000        6154.000   \nN_g                32.000          37.000          36.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 , re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 , re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 , re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 , re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 , re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 , re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.016***        0.014***        0.001   \n                  (0.004)         (0.004)         (0.001)   \ntimesecSto~g       -0.001           0.010           0.003   \n                  (0.011)         (0.010)         (0.003)   \nc.neg#c.ti~g       -0.007**        -0.008***       -0.001*  \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.022           0.022          -0.002   \n                  (0.028)         (0.024)         (0.008)   \nc.neg#c.ri~2       -0.007          -0.001           0.001   \n                  (0.005)         (0.005)         (0.001)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.025***        0.007** \n                  (0.005)         (0.005)         (0.003)   \nfemale             -0.003           0.002           0.001   \n                  (0.006)         (0.005)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.015          -0.014           0.011*  \n                  (0.009)         (0.011)         (0.005)   \nuniversity          0.000          -0.004           0.002   \n                  (0.006)         (0.007)         (0.002)   \n_cons              -0.009          -0.006          -0.019*  \n                  (0.023)         (0.025)         (0.008)   \n------------------------------------------------------------\nr2_w                0.029           0.016           0.002   \nr2_b                0.023           0.044           0.193   \nr2_o                0.027           0.016           0.005   \nN                5472.000        5472.000        8208.000   \nN_g                32.000          32.000          48.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013***        0.004           0.020** \n                  (0.003)         (0.003)         (0.007)   \ntimesecSto~g        0.022*         -0.008           0.016   \n                  (0.009)         (0.007)         (0.017)   \nc.neg#c.ti~g       -0.008***       -0.001          -0.007*  \n                  (0.002)         (0.001)         (0.003)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.014           0.001           0.082   \n                  (0.022)         (0.021)         (0.050)   \nc.neg#c.ri~2        0.006          -0.003          -0.015   \n                  (0.004)         (0.004)         (0.010)   \norder              -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.008          -0.035***       -0.301***\n                  (0.005)         (0.004)         (0.005)   \nfemale              0.005           0.006           0.006   \n                  (0.005)         (0.004)         (0.008)   \nage                -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.026           0.007           0.003   \n                  (0.013)         (0.007)         (0.016)   \nuniversity          0.006          -0.005           0.005   \n                  (0.005)         (0.005)         (0.008)   \n_cons              -0.012           0.010          -0.071   \n                  (0.021)         (0.016)         (0.038)   \n------------------------------------------------------------\nr2_w                0.008           0.014           0.139   \nr2_b                0.318           0.152           0.000   \nr2_o                0.010           0.015           0.135   \nN                5274.000        8160.000       23930.000   \nN_g                31.000          48.000         140.000   \n------------------------------------------------------------\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & wp_right2_ext==1, re  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & wp_right2_ext=\n> =1, re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & wp_right2_ex\n> t==1, re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & wp_right2_ext=\n> =1, re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.009***        0.006           0.004   \n                  (0.002)         (0.006)         (0.013)   \ntimesecSto~g        0.004           0.017           0.032   \n                  (0.005)         (0.015)         (0.037)   \nc.neg#c.ti~g       -0.004***       -0.005           0.000   \n                  (0.001)         (0.003)         (0.007)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.007          -0.033           0.052   \n                  (0.009)         (0.035)         (0.072)   \nc.neg#c.ri~2       -0.001           0.001          -0.002   \n                  (0.002)         (0.006)         (0.014)   \norder               0.000*          0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.129***       -0.003          -0.235***\n                  (0.002)         (0.007)         (0.013)   \nfemale              0.001           0.010          -0.005   \n                  (0.002)         (0.013)         (0.022)   \nage                -0.000           0.000          -0.000   \n                  (0.000)         (0.001)         (0.001)   \nincome             -0.005           0.014          -0.077*  \n                  (0.004)         (0.025)         (0.039)   \nuniversity          0.003          -0.019*          0.055** \n                  (0.002)         (0.009)         (0.019)   \n_cons              -0.019          -0.020          -0.093   \n                  (0.010)         (0.042)         (0.080)   \n------------------------------------------------------------\nr2_w                0.054           0.003           0.116   \nr2_b                0.029           0.476           0.078   \nr2_o                0.052           0.007           0.111   \nN               74334.000        2718.000        2736.000   \nN_g               435.000          16.000          16.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.013**         0.008          -0.001   \n                  (0.005)         (0.005)         (0.003)   \ntimesecSto~g        0.005           0.013          -0.003   \n                  (0.012)         (0.010)         (0.007)   \nc.neg#c.ti~g       -0.007**        -0.007**        -0.001   \n                  (0.002)         (0.002)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.007          -0.031          -0.066** \n                  (0.026)         (0.035)         (0.020)   \nc.neg#c.ri~2       -0.000           0.008           0.012***\n                  (0.005)         (0.006)         (0.003)   \norder               0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.028***       -0.019***       -0.033***\n                  (0.006)         (0.004)         (0.006)   \nfemale             -0.005          -0.006          -0.006   \n                  (0.007)         (0.006)         (0.006)   \nage                -0.000          -0.001*          0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome              0.002           0.003          -0.003   \n                  (0.017)         (0.014)         (0.012)   \nuniversity          0.005           0.008          -0.007   \n                  (0.007)         (0.009)         (0.006)   \n_cons              -0.020           0.014           0.017   \n                  (0.029)         (0.029)         (0.019)   \n------------------------------------------------------------\nr2_w                0.017           0.007           0.017   \nr2_b                0.172           0.231           0.207   \nr2_o                0.017           0.008           0.019   \nN                3249.000        7353.000        3078.000   \nN_g                19.000          43.000          18.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & wp_right2_ext=\n> =1, re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & wp_right2_ex\n> t==1, re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & wp_right2_ex\n> t==1, re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & wp_right2_ext=\n> =1, re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                 0.007           0.003          -0.004          -0.003   \n                  (0.005)         (0.003)         (0.005)         (0.003)   \ntimesecSto~g       -0.005           0.005          -0.026*         -0.005   \n                  (0.014)         (0.006)         (0.011)         (0.008)   \nc.neg#c.ti~g       -0.002          -0.003*          0.002           0.000   \n                  (0.003)         (0.001)         (0.002)         (0.002)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.039          -0.013          -0.011          -0.034   \n                  (0.031)         (0.015)         (0.023)         (0.028)   \nc.neg#c.ri~2       -0.007           0.003           0.003           0.006   \n                  (0.006)         (0.003)         (0.004)         (0.004)   \norder               0.000          -0.000          -0.000          -0.000   \n                  (0.000)         (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.039***       -0.013**        -0.034***       -0.022***\n                  (0.006)         (0.004)         (0.005)         (0.006)   \nfemale              0.004          -0.006          -0.004           0.002   \n                  (0.007)         (0.003)         (0.006)         (0.006)   \nage                 0.000           0.000           0.000          -0.000   \n                  (0.000)         (0.000)         (0.001)         (0.001)   \nincome             -0.035          -0.002          -0.010          -0.009   \n                  (0.018)         (0.005)         (0.017)         (0.014)   \nuniversity          0.017*         -0.004           0.004          -0.008   \n                  (0.007)         (0.004)         (0.008)         (0.008)   \n_cons              -0.017          -0.002           0.032           0.044   \n                  (0.030)         (0.015)         (0.029)         (0.038)   \n----------------------------------------------------------------------------\nr2_w                0.013           0.004           0.013           0.009   \nr2_b                0.268           0.198           0.002           0.097   \nr2_o                0.015           0.005           0.012           0.010   \nN                3933.000        5643.000        4608.000        2394.000   \nN_g                23.000          33.000          27.000          14.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.005           0.004           0.024** \n                  (0.007)         (0.004)         (0.008)   \ntimesecSto~g       -0.006          -0.004           0.009   \n                  (0.019)         (0.011)         (0.021)   \nc.neg#c.ti~g       -0.005          -0.003          -0.012** \n                  (0.004)         (0.002)         (0.004)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.012          -0.030           0.040   \n                  (0.043)         (0.031)         (0.050)   \nc.neg#c.ri~2       -0.002           0.005          -0.003   \n                  (0.007)         (0.006)         (0.009)   \norder               0.000          -0.000           0.000   \n                  (0.001)         (0.000)         (0.001)   \nL.gslmc            -0.034***       -0.041***       -0.057***\n                  (0.007)         (0.007)         (0.006)   \nfemale             -0.004          -0.003           0.010   \n                  (0.014)         (0.007)         (0.010)   \nage                 0.005          -0.000           0.007*  \n                  (0.007)         (0.002)         (0.004)   \nincome             -0.012           0.025           0.005   \n                  (0.048)         (0.018)         (0.017)   \nuniversity         -0.082          -0.007          -0.019   \n                  (0.154)         (0.016)         (0.025)   \n_cons               0.000           0.014          -0.191*  \n                      (.)         (0.053)         (0.085)   \n------------------------------------------------------------\nr2_w                0.013           0.017           0.036   \nr2_b                0.032           0.260           0.333   \nr2_o                0.013           0.019           0.038   \nN                2736.000        3249.000        2907.000   \nN_g                16.000          19.000          17.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & wp_right2_ext=\n> =1, re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & wp_right2_ext=\n> =1, re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.026***        0.022***        0.000   \n                  (0.006)         (0.007)         (0.002)   \ntimesecSto~g        0.012           0.024           0.004   \n                  (0.016)         (0.017)         (0.004)   \nc.neg#c.ti~g       -0.011***       -0.013***       -0.001   \n                  (0.003)         (0.003)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.046           0.034          -0.004   \n                  (0.035)         (0.030)         (0.010)   \nc.neg#c.ri~2       -0.011          -0.002           0.002   \n                  (0.006)         (0.006)         (0.002)   \norder              -0.001           0.000           0.000   \n                  (0.000)         (0.001)         (0.000)   \nL.gslmc            -0.050***       -0.036***        0.009*  \n                  (0.007)         (0.008)         (0.004)   \nfemale             -0.004          -0.006          -0.001   \n                  (0.009)         (0.008)         (0.003)   \nage                 0.000          -0.001           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome              0.000          -0.024           0.011   \n                  (0.016)         (0.017)         (0.007)   \nuniversity         -0.017          -0.027           0.000   \n                  (0.011)         (0.036)         (0.003)   \n_cons              -0.038           0.000          -0.014   \n                  (0.033)             (.)         (0.012)   \n------------------------------------------------------------\nr2_w                0.035           0.021           0.002   \nr2_b                0.022           0.173           0.190   \nr2_o                0.034           0.021           0.003   \nN                3249.000        2907.000        4275.000   \nN_g                19.000          17.000          25.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.010*          0.003           0.018*  \n                  (0.004)         (0.003)         (0.009)   \ntimesecSto~g        0.011          -0.006           0.024   \n                  (0.012)         (0.008)         (0.023)   \nc.neg#c.ti~g       -0.006*         -0.000          -0.009*  \n                  (0.002)         (0.002)         (0.004)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.005           0.001           0.076   \n                  (0.025)         (0.018)         (0.050)   \nc.neg#c.ri~2        0.006          -0.002          -0.012   \n                  (0.004)         (0.003)         (0.010)   \norder              -0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc             0.041***       -0.034***       -0.305***\n                  (0.006)         (0.005)         (0.007)   \nfemale              0.004           0.004           0.009   \n                  (0.015)         (0.005)         (0.010)   \nage                -0.000          -0.000          -0.001   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.031           0.007           0.006   \n                  (0.025)         (0.012)         (0.021)   \nuniversity          0.012          -0.005           0.017   \n                  (0.010)         (0.006)         (0.011)   \n_cons               0.005           0.008          -0.077   \n                  (0.036)         (0.018)         (0.048)   \n------------------------------------------------------------\nr2_w                0.023           0.013           0.141   \nr2_b                0.522           0.235           0.067   \nr2_o                0.031           0.015           0.136   \nN                2556.000        4095.000       12648.000   \nN_g                15.000          24.000          74.000   \n------------------------------------------------------------\n.   \n.   xtset resp timesec\n       panel variable:  resp (unbalanced)\n        time variable:  timesec, 1 to 565\n                delta:  1 unit\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if period==2 & political_interest_dichox==1, r\n> e  \n.   estimates store G\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"BR\" & period==2 & political_inte\n> rest_dichox==1, re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CA.f\" & period==2 & political_in\n> terest_dichox==1, re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CH\" & period==2 & political_inte\n> rest_dichox==1, re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"CN\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"DK\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store F \n.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.012***        0.009           0.016   \n                  (0.002)         (0.006)         (0.009)   \ntimesecSto~g        0.012*          0.020           0.032   \n                  (0.005)         (0.017)         (0.024)   \nc.neg#c.ti~g       -0.006***       -0.007*         -0.007   \n                  (0.001)         (0.003)         (0.005)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.014          -0.034           0.063   \n                  (0.011)         (0.049)         (0.058)   \nc.neg#c.ri~2       -0.002           0.000          -0.001   \n                  (0.002)         (0.008)         (0.011)   \norder               0.000**         0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.132***       -0.025***       -0.175***\n                  (0.002)         (0.007)         (0.009)   \nfemale              0.003          -0.004           0.016   \n                  (0.002)         (0.012)         (0.013)   \nage                -0.000          -0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.009           0.008          -0.047   \n                  (0.005)         (0.026)         (0.025)   \nuniversity          0.005          -0.015           0.032*  \n                  (0.003)         (0.013)         (0.013)   \n_cons              -0.039***        0.010          -0.095   \n                  (0.012)         (0.044)         (0.051)   \n------------------------------------------------------------\nr2_w                0.057           0.009           0.087   \nr2_b                0.017           0.223           0.027   \nr2_o                0.054           0.011           0.083   \nN               64760.000        3069.000        4275.000   \nN_g               379.000          18.000          25.000   \n------------------------------------------------------------\n.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.014           0.005           0.006   \n                  (0.007)         (0.005)         (0.003)   \ntimesecSto~g        0.002           0.014           0.006   \n                  (0.019)         (0.010)         (0.008)   \nc.neg#c.ti~g       -0.006          -0.006***       -0.004*  \n                  (0.004)         (0.002)         (0.002)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.003          -0.060          -0.057*  \n                  (0.047)         (0.037)         (0.023)   \nc.neg#c.ri~2       -0.001           0.016*          0.012** \n                  (0.009)         (0.007)         (0.004)   \norder               0.000          -0.000           0.000   \n                  (0.001)         (0.000)         (0.000)   \nL.gslmc            -0.028***       -0.032***       -0.035***\n                  (0.007)         (0.004)         (0.007)   \nfemale             -0.002          -0.006           0.001   \n                  (0.011)         (0.006)         (0.006)   \nage                 0.001          -0.001          -0.000   \n                  (0.000)         (0.001)         (0.000)   \nincome             -0.064          -0.001          -0.000   \n                  (0.037)         (0.014)         (0.009)   \nuniversity         -0.005           0.007          -0.002   \n                  (0.013)         (0.007)         (0.005)   \n_cons              -0.020           0.010          -0.008   \n                  (0.043)         (0.030)         (0.018)   \n------------------------------------------------------------\nr2_w                0.013           0.013           0.020   \nr2_b                0.299           0.194           0.140   \nr2_o                0.014           0.014           0.021   \nN                2565.000        7011.000        2736.000   \nN_g                15.000          41.000          16.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"FR\" & period==2 & political_inte\n> rest_dichox==1, re  \n.   estimates store A\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"GH\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IN\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.j\" & period==2 & political_in\n> terest_dichox==1, re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IS.p\" & period==2 & political_in\n> terest_dichox==1, re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"IT\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"JP\" & period==2 & political_inte\n> rest_dichox==1, re  \n.   estimates store G\n.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b \n> r2_o N N_g) \n\n----------------------------------------------------------------------------\n                      (1)             (2)             (3)             (4)   \n                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se            b/se   \n----------------------------------------------------------------------------\nneg                -0.002           0.001          -0.004           0.016   \n                  (0.007)         (0.003)         (0.005)         (0.009)   \ntimesecSto~g       -0.016          -0.005          -0.019           0.028   \n                  (0.017)         (0.006)         (0.011)         (0.025)   \nc.neg#c.ti~g        0.002          -0.001           0.002          -0.008   \n                  (0.003)         (0.001)         (0.002)         (0.005)   \nneg                 0.000           0.000           0.000           0.000   \n                      (.)             (.)             (.)             (.)   \nright2              0.075          -0.009          -0.023           0.032   \n                  (0.053)         (0.018)         (0.027)         (0.077)   \nc.neg#c.ri~2       -0.001           0.001           0.001          -0.006   \n                  (0.009)         (0.003)         (0.005)         (0.014)   \norder              -0.000           0.000          -0.000          -0.000   \n                  (0.001)         (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.013           0.010*         -0.043***       -0.072***\n                  (0.007)         (0.004)         (0.005)         (0.011)   \nfemale             -0.003          -0.004           0.005           0.015   \n                  (0.011)         (0.004)         (0.008)         (0.021)   \nage                -0.001           0.000           0.000           0.000   \n                  (0.001)         (0.000)         (0.000)         (0.001)   \nincome             -0.012          -0.001          -0.013           0.008   \n                  (0.021)         (0.007)         (0.014)         (0.022)   \nuniversity          0.009          -0.001           0.010          -0.076   \n                  (0.011)         (0.004)         (0.007)         (0.059)   \n_cons               0.028           0.008           0.034           0.000   \n                  (0.040)         (0.020)         (0.029)             (.)   \n----------------------------------------------------------------------------\nr2_w                0.002           0.004           0.016           0.031   \nr2_b                0.281           0.029           0.009           0.323   \nr2_o                0.006           0.004           0.016           0.031   \nN                3078.000        4788.000        4275.000        1539.000   \nN_g                18.000          28.000          25.000           9.000   \n----------------------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.011           0.006           0.033***\n                  (0.007)         (0.005)         (0.008)   \ntimesecSto~g        0.019           0.014           0.024   \n                  (0.017)         (0.013)         (0.021)   \nc.neg#c.ti~g       -0.009**        -0.005          -0.015***\n                  (0.003)         (0.003)         (0.004)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.015           0.031           0.059   \n                  (0.056)         (0.050)         (0.064)   \nc.neg#c.ri~2        0.005           0.001          -0.014   \n                  (0.011)         (0.009)         (0.011)   \norder               0.001           0.000          -0.000   \n                  (0.001)         (0.000)         (0.001)   \nL.gslmc            -0.017**        -0.018*         -0.050***\n                  (0.006)         (0.008)         (0.006)   \nfemale             -0.012           0.013           0.032*  \n                  (0.010)         (0.008)         (0.015)   \nage                 0.004           0.001*          0.005   \n                  (0.002)         (0.001)         (0.004)   \nincome              0.014          -0.013           0.039   \n                  (0.025)         (0.024)         (0.029)   \nuniversity         -0.113*         -0.002          -0.215*  \n                  (0.057)         (0.014)         (0.107)   \n_cons               0.000          -0.052           0.000   \n                      (.)         (0.037)             (.)   \n------------------------------------------------------------\nr2_w                0.008           0.006           0.035   \nr2_b                0.183           0.628           0.333   \nr2_o                0.009           0.012           0.037   \nN                3249.000        2223.000        2907.000   \nN_g                19.000          13.000          17.000   \n------------------------------------------------------------\n.   \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"NZ\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store B\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"RU\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store C  \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SE\" & period==2 & political_inte\n> rest_dichox==1, re  \n.   estimates store D\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"SW\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store E\n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"UK\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store F \n.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm\n> c female age income university if country2==\"US\" & period==2 & political_inte\n> rest_dichox==1, re   \n.   estimates store G \n.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.007           0.014*          0.001   \n                  (0.005)         (0.007)         (0.002)   \ntimesecSto~g       -0.012           0.017          -0.000   \n                  (0.012)         (0.015)         (0.004)   \nc.neg#c.ti~g       -0.003          -0.008**        -0.001   \n                  (0.002)         (0.003)         (0.001)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2              0.023           0.018           0.009   \n                  (0.030)         (0.031)         (0.011)   \nc.neg#c.ri~2       -0.005          -0.001           0.000   \n                  (0.006)         (0.006)         (0.002)   \norder               0.000          -0.001           0.000   \n                  (0.000)         (0.000)         (0.000)   \nL.gslmc            -0.046***       -0.016*          0.010** \n                  (0.007)         (0.007)         (0.004)   \nfemale             -0.003           0.012           0.003   \n                  (0.007)         (0.007)         (0.002)   \nage                -0.000          -0.000           0.000   \n                  (0.000)         (0.000)         (0.000)   \nincome             -0.021          -0.028           0.009   \n                  (0.013)         (0.017)         (0.008)   \nuniversity          0.011          -0.003           0.004   \n                  (0.008)         (0.014)         (0.002)   \n_cons               0.018          -0.012          -0.022   \n                  (0.027)         (0.038)         (0.012)   \n------------------------------------------------------------\nr2_w                0.023           0.010           0.003   \nr2_b                0.017           0.395           0.240   \nr2_o                0.022           0.012           0.006   \nN                3420.000        2736.000        4617.000   \nN_g                20.000          16.000          27.000   \n------------------------------------------------------------\n.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2\n> _o N N_g) \n\n------------------------------------------------------------\n                      (1)             (2)             (3)   \n                  D.gslmc         D.gslmc         D.gslmc   \n                     b/se            b/se            b/se   \n------------------------------------------------------------\nneg                 0.006           0.003           0.034*  \n                  (0.004)         (0.004)         (0.013)   \ntimesecSto~g        0.003           0.005           0.056   \n                  (0.011)         (0.010)         (0.035)   \nc.neg#c.ti~g       -0.004          -0.003          -0.012   \n                  (0.002)         (0.002)         (0.007)   \nneg                 0.000           0.000           0.000   \n                      (.)             (.)             (.)   \nright2             -0.020          -0.012           0.163   \n                  (0.024)         (0.029)         (0.093)   \nc.neg#c.ri~2        0.004           0.005          -0.022   \n                  (0.004)         (0.005)         (0.018)   \norder              -0.000           0.000           0.001   \n                  (0.000)         (0.000)         (0.001)   \nL.gslmc            -0.015          -0.093***       -0.361***\n                  (0.008)         (0.008)         (0.009)   \nfemale             -0.002          -0.000           0.007   \n                  (0.010)         (0.006)         (0.016)   \nage                 0.000          -0.000          -0.001   \n                  (0.000)         (0.000)         (0.001)   \nincome             -0.001          -0.006          -0.038   \n                  (0.018)         (0.015)         (0.035)   \nuniversity         -0.004          -0.003           0.022   \n                  (0.008)         (0.007)         (0.018)   \n_cons              -0.004           0.003          -0.156*  \n                  (0.025)         (0.023)         (0.076)   \n------------------------------------------------------------\nr2_w                0.011           0.053           0.173   \nr2_b                0.205           0.298           0.005   \nr2_o                0.011           0.055           0.166   \nN                1872.000        2709.000        7520.000   \nN_g                11.000          16.000          44.000   \n------------------------------------------------------------\n"} -->
<pre><code>. *** Syntax for analyses of time-series photo data
. *** Use data file 'Time-series-data-photos.dta' with this syntax
. * Table 5 Columns 5 , 6 and 7
.  
.   gen neg = .
(449,554 missing values generated)
.   replace neg = negativity
(309,058 real changes made)
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc
&gt; ome university if wp_right2_dichox==0 &amp; period==2 , re  
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog order L.gslmc female age inc
&gt; ome university if wp_right2_dichox==1 &amp; period==2 , re  
.   estimates store C
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.wp_right2 order L.g
&gt; slmc female age income university if period==2 , re    
.   estimates store D  
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011***        0.007***        0.010***
                  (0.002)         (0.002)         (0.001)   
timesecSto~g        0.005          -0.001           0.002   
                  (0.005)         (0.005)         (0.004)   
c.neg#c.ti~g       -0.005***       -0.003**        -0.004***
                  (0.001)         (0.001)         (0.001)   
order               0.000*          0.000           0.000*  
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.128***       -0.133***       -0.131***
                  (0.002)         (0.002)         (0.002)   
female              0.003           0.002           0.003   
                  (0.002)         (0.002)         (0.002)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.000          -0.012*         -0.006   
                  (0.005)         (0.005)         (0.003)   
university         -0.001           0.004           0.002   
                  (0.002)         (0.002)         (0.002)   
neg                                                 0.000   
                                                      (.)   
wp_right2                                           0.013   
                                                  (0.008)   
c.neg#c.wp~2                                       -0.002   
                                                  (0.002)   
_cons              -0.023*         -0.007          -0.020*  
                  (0.010)         (0.010)         (0.008)   
------------------------------------------------------------
r2_w                0.057           0.053           0.055   
r2_b                0.043           0.007           0.006   
r2_o                0.054           0.052           0.053   
N               70213.000       67823.000      138036.000   
N_g               411.000         397.000         808.000   
------------------------------------------------------------
.   
.   
. * Table 6 Column 2
.   
.   gen right2 = .
(449,554 missing values generated)
.   replace right2= wp_right2
(446,870 real changes made)
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014**         0.013           0.010*  
                  (0.004)         (0.008)         (0.004)   
timesecSto~g        0.026*          0.031          -0.001   
                  (0.011)         (0.023)         (0.011)   
c.neg#c.ti~g       -0.009***       -0.006          -0.005** 
                  (0.002)         (0.005)         (0.002)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.035           0.055          -0.009   
                  (0.033)         (0.055)         (0.028)   
c.neg#c.ri~2        0.000          -0.002          -0.001   
                  (0.006)         (0.011)         (0.005)   
order               0.000           0.001           0.000   
                  (0.000)         (0.001)         (0.000)   
L.gslmc            -0.028***       -0.186***       -0.021***
                  (0.005)         (0.009)         (0.004)   
female              0.005           0.013           0.005   
                  (0.006)         (0.012)         (0.005)   
age                -0.000          -0.000           0.000   
                  (0.001)         (0.000)         (0.000)   
income             -0.001          -0.048*         -0.015   
                  (0.014)         (0.024)         (0.014)   
university         -0.001           0.040**        -0.003   
                  (0.006)         (0.013)         (0.005)   
_cons              -0.032          -0.096          -0.003   
                  (0.028)         (0.050)         (0.024)   
------------------------------------------------------------
r2_w                0.010           0.092           0.011   
r2_b                0.137           0.023           0.096   
r2_o                0.011           0.088           0.011   
N                5607.000        4617.000        6156.000   
N_g                33.000          27.000          36.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.008           0.000           0.004   
                  (0.004)         (0.002)         (0.004)   
timesecSto~g        0.011          -0.001          -0.015   
                  (0.009)         (0.005)         (0.011)   
c.neg#c.ti~g       -0.006***       -0.001          -0.000   
                  (0.002)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.032          -0.049**         0.053   
                  (0.034)         (0.017)         (0.032)   
c.neg#c.ri~2        0.008           0.009**        -0.005   
                  (0.006)         (0.003)         (0.006)   
order              -0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.018***       -0.038***
                  (0.003)         (0.004)         (0.004)   
female             -0.005          -0.004           0.005   
                  (0.004)         (0.003)         (0.005)   
age                -0.001*          0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.002          -0.003          -0.020   
                  (0.012)         (0.007)         (0.013)   
university          0.010          -0.003           0.014** 
                  (0.007)         (0.003)         (0.005)   
_cons               0.010           0.006          -0.003   
                  (0.026)         (0.012)         (0.026)   
------------------------------------------------------------
r2_w                0.008           0.009           0.011   
r2_b                0.240           0.004           0.105   
r2_o                0.009           0.008           0.012   
N                9747.000        5985.000        8721.000   
N_g                57.000          35.000          51.000   
------------------------------------------------------------
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.001          -0.003           0.001   
                  (0.003)         (0.003)         (0.004)   
timesecSto~g       -0.005          -0.016*         -0.010   
                  (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.001           0.001          -0.000   
                  (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.013          -0.009           0.035   
                  (0.016)         (0.018)         (0.030)   
c.neg#c.ri~2        0.003           0.002          -0.002   
                  (0.003)         (0.003)         (0.005)   
order              -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.023***       -0.030***       -0.053***
                  (0.003)         (0.004)         (0.006)   
female             -0.006*         -0.002           0.004   
                  (0.002)         (0.004)         (0.006)   
age                 0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
income              0.001          -0.011           0.003   
                  (0.005)         (0.008)         (0.011)   
university         -0.001           0.004           0.001   
                  (0.002)         (0.004)         (0.008)   
_cons               0.019           0.023          -0.021   
                  (0.014)         (0.018)         (0.031)   
------------------------------------------------------------
r2_w                0.008           0.010           0.021   
r2_b                0.082           0.000           0.009   
r2_o                0.008           0.010           0.020   
N               10260.000        8199.000        4104.000   
N_g                60.000          48.000          24.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.004           0.020***
                  (0.005)         (0.003)         (0.006)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.015          -0.012           0.020   
                  (0.036)         (0.028)         (0.047)   
c.neg#c.ri~2       -0.000           0.004          -0.004   
                  (0.007)         (0.005)         (0.009)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.003           0.000           0.004   
                  (0.008)         (0.005)         (0.008)   
age                 0.005*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.007           0.020           0.014   
                  (0.019)         (0.013)         (0.015)   
university         -0.003          -0.003          -0.026*  
                  (0.022)         (0.007)         (0.012)   
_cons              -0.111*         -0.016          -0.052   
                  (0.051)         (0.023)         (0.064)   
------------------------------------------------------------
r2_w                0.009           0.014           0.021   
r2_b                0.160           0.184           0.034   
r2_o                0.010           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.014***        0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.001           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.022           0.022          -0.002   
                  (0.028)         (0.024)         (0.008)   
c.neg#c.ri~2       -0.007          -0.001           0.001   
                  (0.005)         (0.005)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007** 
                  (0.005)         (0.005)         (0.003)   
female             -0.003           0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.014           0.011*  
                  (0.009)         (0.011)         (0.005)   
university          0.000          -0.004           0.002   
                  (0.006)         (0.007)         (0.002)   
_cons              -0.009          -0.006          -0.019*  
                  (0.023)         (0.025)         (0.008)   
------------------------------------------------------------
r2_w                0.029           0.016           0.002   
r2_b                0.023           0.044           0.193   
r2_o                0.027           0.016           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.004           0.020** 
                  (0.003)         (0.003)         (0.007)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.014           0.001           0.082   
                  (0.022)         (0.021)         (0.050)   
c.neg#c.ri~2        0.006          -0.003          -0.015   
                  (0.004)         (0.004)         (0.010)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.005           0.006           0.006   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.026           0.007           0.003   
                  (0.013)         (0.007)         (0.016)   
university          0.006          -0.005           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.012           0.010          -0.071   
                  (0.021)         (0.016)         (0.038)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.318           0.152           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
. * Table A4 Row 3 
.  
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; (negative==1 | negative==0) , r
&gt; e  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; (negative==1
&gt;  | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010***        0.014**         0.013   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.013          -0.035           0.055   
                  (0.008)         (0.033)         (0.055)   
c.neg#c.ri~2       -0.002           0.000          -0.002   
                  (0.002)         (0.006)         (0.011)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.028***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.005           0.013   
                  (0.002)         (0.006)         (0.012)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006          -0.001          -0.048*  
                  (0.003)         (0.014)         (0.024)   
university          0.002          -0.001           0.040** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.020*         -0.032          -0.096   
                  (0.008)         (0.028)         (0.050)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.137           0.023   
r2_o                0.053           0.011           0.088   
N              138036.000        5607.000        4617.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.008           0.000   
                  (0.004)         (0.004)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.009          -0.032          -0.049** 
                  (0.028)         (0.034)         (0.017)   
c.neg#c.ri~2       -0.001           0.008           0.009** 
                  (0.005)         (0.006)         (0.003)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.005          -0.005          -0.004   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.002          -0.003   
                  (0.014)         (0.012)         (0.007)   
university         -0.003           0.010          -0.003   
                  (0.005)         (0.007)         (0.003)   
_cons              -0.003           0.010           0.006   
                  (0.024)         (0.026)         (0.012)   
------------------------------------------------------------
r2_w                0.011           0.008           0.009   
r2_b                0.096           0.240           0.004   
r2_o                0.011           0.009           0.008   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; (negative==1
&gt;  | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; (negative==1
&gt;  | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004           0.001          -0.003           0.001   
                  (0.004)         (0.003)         (0.003)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.053          -0.013          -0.009           0.035   
                  (0.032)         (0.016)         (0.018)         (0.030)   
c.neg#c.ri~2       -0.005           0.003           0.002          -0.002   
                  (0.006)         (0.003)         (0.003)         (0.005)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.053***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.005          -0.006*         -0.002           0.004   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.020           0.001          -0.011           0.003   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.014**        -0.001           0.004           0.001   
                  (0.005)         (0.002)         (0.004)         (0.008)   
_cons              -0.003           0.019           0.023          -0.021   
                  (0.026)         (0.014)         (0.018)         (0.031)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.010           0.021   
r2_b                0.105           0.082           0.000           0.009   
r2_o                0.012           0.008           0.010           0.020   
N                8721.000       10260.000        8199.000        4104.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.004           0.020***
                  (0.005)         (0.003)         (0.006)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.015          -0.012           0.020   
                  (0.036)         (0.028)         (0.047)   
c.neg#c.ri~2       -0.000           0.004          -0.004   
                  (0.007)         (0.005)         (0.009)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.003           0.000           0.004   
                  (0.008)         (0.005)         (0.008)   
age                 0.005*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.007           0.020           0.014   
                  (0.019)         (0.013)         (0.015)   
university         -0.003          -0.003          -0.026*  
                  (0.022)         (0.007)         (0.012)   
_cons              -0.111*         -0.016          -0.052   
                  (0.051)         (0.023)         (0.064)   
------------------------------------------------------------
r2_w                0.009           0.014           0.021   
r2_b                0.160           0.184           0.034   
r2_o                0.010           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; (negative==1 |
&gt;  negative==0) , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.014***        0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.001           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.022           0.022          -0.002   
                  (0.028)         (0.024)         (0.008)   
c.neg#c.ri~2       -0.007          -0.001           0.001   
                  (0.005)         (0.005)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007** 
                  (0.005)         (0.005)         (0.003)   
female             -0.003           0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.014           0.011*  
                  (0.009)         (0.011)         (0.005)   
university          0.000          -0.004           0.002   
                  (0.006)         (0.007)         (0.002)   
_cons              -0.009          -0.006          -0.019*  
                  (0.023)         (0.025)         (0.008)   
------------------------------------------------------------
r2_w                0.029           0.016           0.002   
r2_b                0.023           0.044           0.193   
r2_o                0.027           0.016           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.004           0.020** 
                  (0.003)         (0.003)         (0.007)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.014           0.001           0.082   
                  (0.022)         (0.021)         (0.050)   
c.neg#c.ri~2        0.006          -0.003          -0.015   
                  (0.004)         (0.004)         (0.010)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.005           0.006           0.006   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.026           0.007           0.003   
                  (0.013)         (0.007)         (0.016)   
university          0.006          -0.005           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.012           0.010          -0.071   
                  (0.021)         (0.016)         (0.038)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.318           0.152           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; (threatening==1 | negative==0) 
&gt; , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; (threatening
&gt; ==1 | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011***        0.013*          0.016   
                  (0.002)         (0.005)         (0.010)   
timesecSto~g        0.003           0.026*          0.032   
                  (0.004)         (0.012)         (0.024)   
c.neg#c.ti~g       -0.005***       -0.008**        -0.006   
                  (0.001)         (0.003)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.015          -0.036           0.061   
                  (0.009)         (0.035)         (0.058)   
c.neg#c.ri~2       -0.003           0.001          -0.003   
                  (0.002)         (0.007)         (0.013)   
order               0.001***        0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.140***       -0.016**        -0.182***
                  (0.002)         (0.006)         (0.010)   
female              0.001           0.004           0.017   
                  (0.002)         (0.007)         (0.014)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.004          -0.001          -0.061*  
                  (0.004)         (0.016)         (0.027)   
university          0.003           0.001           0.047** 
                  (0.002)         (0.007)         (0.015)   
_cons              -0.028**        -0.031          -0.104   
                  (0.009)         (0.031)         (0.054)   
------------------------------------------------------------
r2_w                0.060           0.005           0.095   
r2_b                0.001           0.109           0.007   
r2_o                0.057           0.006           0.088   
N              108968.000        4428.000        3645.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g)

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.008           0.001          -0.001   
                  (0.005)         (0.005)         (0.002)   
timesecSto~g       -0.006           0.002          -0.005   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.003          -0.003           0.000   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.000          -0.025          -0.041*  
                  (0.030)         (0.034)         (0.016)   
c.neg#c.ri~2       -0.005           0.009           0.007*  
                  (0.006)         (0.007)         (0.003)   
order               0.001          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.020***       -0.028***       -0.016***
                  (0.005)         (0.004)         (0.005)   
female              0.005          -0.010*         -0.002   
                  (0.006)         (0.005)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.018           0.006          -0.004   
                  (0.017)         (0.012)         (0.007)   
university         -0.003           0.006          -0.001   
                  (0.006)         (0.007)         (0.003)   
_cons              -0.002           0.028           0.007   
                  (0.025)         (0.027)         (0.012)   
------------------------------------------------------------
r2_w                0.008           0.008           0.006   
r2_b                0.039           0.227           0.018   
r2_o                0.008           0.009           0.006   
N                4860.000        7695.000        4725.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; (threatening
&gt; ==1 | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; (threatening
&gt; ==1 | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.002           0.003           0.001           0.002   
                  (0.005)         (0.003)         (0.004)         (0.005)   
timesecSto~g       -0.016          -0.003          -0.016*         -0.005   
                  (0.011)         (0.006)         (0.007)         (0.012)   
c.neg#c.ti~g        0.000          -0.002*          0.001          -0.002   
                  (0.002)         (0.001)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.024          -0.008           0.008           0.035   
                  (0.035)         (0.016)         (0.018)         (0.031)   
c.neg#c.ri~2        0.006           0.001          -0.004           0.005   
                  (0.007)         (0.004)         (0.004)         (0.006)   
order               0.000          -0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.042***       -0.022***       -0.037***       -0.043***
                  (0.005)         (0.004)         (0.004)         (0.007)   
female              0.006          -0.005          -0.002           0.005   
                  (0.007)         (0.003)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.002*  
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.035          -0.000          -0.009           0.009   
                  (0.018)         (0.005)         (0.009)         (0.013)   
university          0.015*         -0.003           0.007           0.003   
                  (0.007)         (0.003)         (0.005)         (0.009)   
_cons               0.017           0.014           0.012          -0.060   
                  (0.028)         (0.015)         (0.019)         (0.034)   
----------------------------------------------------------------------------
r2_w                0.013           0.009           0.016           0.018   
r2_b                0.122           0.039           0.003           0.131   
r2_o                0.015           0.009           0.015           0.018   
N                6885.000        8100.000        6480.000        3240.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.005           0.002           0.020** 
                  (0.006)         (0.003)         (0.006)   
timesecSto~g        0.003          -0.008           0.004   
                  (0.013)         (0.008)         (0.014)   
c.neg#c.ti~g       -0.005          -0.002          -0.010***
                  (0.003)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.012          -0.007           0.001   
                  (0.035)         (0.029)         (0.045)   
c.neg#c.ri~2        0.001           0.003          -0.002   
                  (0.008)         (0.006)         (0.010)   
order               0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.027***       -0.045***
                  (0.006)         (0.005)         (0.005)   
female             -0.003          -0.001          -0.002   
                  (0.007)         (0.005)         (0.007)   
age                 0.004*          0.001*          0.001   
                  (0.002)         (0.000)         (0.002)   
income              0.011           0.013           0.000   
                  (0.018)         (0.013)         (0.014)   
university         -0.005          -0.003           0.001   
                  (0.020)         (0.007)         (0.011)   
_cons              -0.081          -0.010          -0.040   
                  (0.048)         (0.023)         (0.060)   
------------------------------------------------------------
r2_w                0.006           0.009           0.025   
r2_b                0.183           0.256           0.020   
r2_o                0.007           0.012           0.024   
N                4320.000        4995.000        4860.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; (threatening==
&gt; 1 | negative==0) , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.017***        0.002   
                  (0.005)         (0.005)         (0.002)   
timesecSto~g       -0.002           0.013           0.004   
                  (0.011)         (0.011)         (0.003)   
c.neg#c.ti~g       -0.006**        -0.009***       -0.002*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.015           0.024           0.000   
                  (0.028)         (0.025)         (0.009)   
c.neg#c.ri~2       -0.004          -0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.040***       -0.023***        0.005   
                  (0.006)         (0.006)         (0.003)   
female             -0.005           0.002           0.002   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.012          -0.007           0.008   
                  (0.010)         (0.013)         (0.006)   
university          0.005          -0.005           0.003   
                  (0.006)         (0.008)         (0.002)   
_cons              -0.009          -0.017          -0.022** 
                  (0.024)         (0.027)         (0.008)   
------------------------------------------------------------
r2_w                0.025           0.014           0.003   
r2_b                0.000           0.055           0.165   
r2_o                0.024           0.014           0.005   
N                4320.000        4320.000        6480.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.006           0.027** 
                  (0.004)         (0.003)         (0.008)   
timesecSto~g        0.026**        -0.006           0.022   
                  (0.010)         (0.008)         (0.018)   
c.neg#c.ti~g       -0.010***       -0.002          -0.010*  
                  (0.002)         (0.002)         (0.004)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.012          -0.002           0.085   
                  (0.022)         (0.021)         (0.054)   
c.neg#c.ri~2        0.003          -0.001          -0.015   
                  (0.005)         (0.005)         (0.012)   
order               0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.012*         -0.043***       -0.316***
                  (0.006)         (0.004)         (0.006)   
female              0.003           0.002           0.001   
                  (0.005)         (0.004)         (0.009)   
age                -0.000          -0.000          -0.001*  
                  (0.000)         (0.000)         (0.000)   
income             -0.009           0.001           0.015   
                  (0.012)         (0.008)         (0.018)   
university         -0.002          -0.003           0.013   
                  (0.005)         (0.005)         (0.009)   
_cons              -0.037           0.010          -0.096*  
                  (0.021)         (0.017)         (0.042)   
------------------------------------------------------------
r2_w                0.009           0.020           0.146   
r2_b                0.099           0.061           0.016   
r2_o                0.009           0.020           0.142   
N                4158.000        6432.000       18890.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; (disgusting==1 | negative==0) ,
&gt;  re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; (disgusting=
&gt; =1 | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.007***        0.009           0.009   
                  (0.002)         (0.005)         (0.010)   
timesecSto~g       -0.001           0.025*          0.025   
                  (0.004)         (0.011)         (0.024)   
c.neg#c.ti~g       -0.003**        -0.007**        -0.003   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.013          -0.048           0.066   
                  (0.009)         (0.032)         (0.058)   
c.neg#c.ri~2       -0.002           0.006          -0.006   
                  (0.002)         (0.007)         (0.013)   
order               0.000***        0.001**         0.002*  
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.134***       -0.022***       -0.204***
                  (0.002)         (0.006)         (0.011)   
female              0.001           0.006           0.013   
                  (0.002)         (0.007)         (0.015)   
age                -0.000           0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.005          -0.004          -0.026   
                  (0.004)         (0.015)         (0.028)   
university          0.001          -0.001           0.038*  
                  (0.002)         (0.007)         (0.015)   
_cons              -0.015          -0.055          -0.104   
                  (0.009)         (0.029)         (0.054)   
------------------------------------------------------------
r2_w                0.058           0.008           0.099   
r2_b                0.041           0.031           0.007   
r2_o                0.053           0.008           0.094   
N              101695.000        4131.000        3402.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014**         0.009           0.001   
                  (0.005)         (0.005)         (0.002)   
timesecSto~g        0.002           0.014           0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.002*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.006          -0.036          -0.058***
                  (0.029)         (0.035)         (0.017)   
c.neg#c.ri~2       -0.002           0.011           0.012***
                  (0.006)         (0.008)         (0.003)   
order               0.000           0.000           0.000** 
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.015**        -0.021***       -0.020***
                  (0.005)         (0.004)         (0.004)   
female              0.004          -0.005          -0.006   
                  (0.006)         (0.005)         (0.004)   
age                -0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.004          -0.021           0.001   
                  (0.016)         (0.013)         (0.008)   
university         -0.006           0.016*         -0.005   
                  (0.006)         (0.008)         (0.004)   
_cons              -0.013           0.005           0.002   
                  (0.025)         (0.028)         (0.012)   
------------------------------------------------------------
r2_w                0.010           0.009           0.013   
r2_b                0.002           0.125           0.010   
r2_o                0.010           0.009           0.012   
N                4536.000        7182.000        4410.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; (disgusting=
&gt; =1 | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; (disgusting=
&gt; =1 | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.005          -0.001          -0.008*         -0.002   
                  (0.005)         (0.003)         (0.003)         (0.005)   
timesecSto~g       -0.018          -0.007          -0.020**        -0.018   
                  (0.010)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g        0.002          -0.000           0.003*          0.003   
                  (0.002)         (0.001)         (0.002)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.067*         -0.017          -0.016           0.047   
                  (0.030)         (0.016)         (0.019)         (0.031)   
c.neg#c.ri~2       -0.012           0.003           0.006          -0.007   
                  (0.006)         (0.004)         (0.004)         (0.006)   
order               0.000          -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.034***       -0.021***       -0.042***       -0.059***
                  (0.005)         (0.004)         (0.004)         (0.007)   
female              0.002          -0.004          -0.003           0.004   
                  (0.005)         (0.003)         (0.005)         (0.006)   
age                 0.000           0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.015           0.003          -0.009           0.009   
                  (0.013)         (0.006)         (0.011)         (0.013)   
university          0.013*          0.002           0.004          -0.003   
                  (0.005)         (0.003)         (0.006)         (0.009)   
_cons              -0.016           0.019           0.032          -0.018   
                  (0.024)         (0.015)         (0.020)         (0.034)   
----------------------------------------------------------------------------
r2_w                0.010           0.007           0.019           0.027   
r2_b                0.073           0.012           0.004           0.005   
r2_o                0.011           0.006           0.018           0.025   
N                6426.000        7560.000        6039.000        3024.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014*          0.002           0.018*  
                  (0.006)         (0.003)         (0.007)   
timesecSto~g        0.010          -0.006          -0.002   
                  (0.014)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007*         -0.002          -0.007*  
                  (0.003)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.027          -0.011           0.023   
                  (0.039)         (0.030)         (0.048)   
c.neg#c.ri~2       -0.005           0.004          -0.006   
                  (0.008)         (0.006)         (0.010)   
order               0.000           0.001          -0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.021***       -0.052***       -0.034***
                  (0.006)         (0.006)         (0.005)   
female             -0.010          -0.002           0.000   
                  (0.009)         (0.006)         (0.008)   
age                 0.007**         0.000           0.001   
                  (0.002)         (0.000)         (0.003)   
income              0.011           0.023           0.025   
                  (0.022)         (0.017)         (0.016)   
university         -0.004           0.000          -0.048***
                  (0.025)         (0.009)         (0.013)   
_cons              -0.158**        -0.008          -0.000   
                  (0.059)         (0.026)         (0.068)   
------------------------------------------------------------
r2_w                0.007           0.022           0.017   
r2_b                0.163           0.002           0.144   
r2_o                0.009           0.020           0.018   
N                4032.000        4662.000        4534.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; (disgusting==1
&gt;  | negative==0) , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012**         0.010*         -0.000   
                  (0.004)         (0.005)         (0.001)   
timesecSto~g       -0.005           0.003           0.001   
                  (0.010)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.005*         -0.005*         -0.000   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.018           0.023          -0.002   
                  (0.026)         (0.023)         (0.009)   
c.neg#c.ri~2       -0.006          -0.001           0.001   
                  (0.006)         (0.005)         (0.002)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.053***       -0.027***        0.015***
                  (0.006)         (0.006)         (0.003)   
female             -0.003          -0.005           0.000   
                  (0.006)         (0.005)         (0.002)   
age                 0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.020*         -0.017           0.014*  
                  (0.010)         (0.013)         (0.006)   
university         -0.003          -0.005           0.000   
                  (0.006)         (0.008)         (0.002)   
_cons              -0.005           0.011          -0.018*  
                  (0.022)         (0.025)         (0.008)   
------------------------------------------------------------
r2_w                0.031           0.011           0.004   
r2_b                0.013           0.022           0.173   
r2_o                0.028           0.011           0.008   
N                4032.000        4032.000        6048.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009*          0.000           0.015   
                  (0.004)         (0.003)         (0.008)   
timesecSto~g        0.020*         -0.012           0.009   
                  (0.009)         (0.008)         (0.018)   
c.neg#c.ti~g       -0.007***        0.001          -0.004   
                  (0.002)         (0.002)         (0.004)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.020           0.004           0.086   
                  (0.020)         (0.021)         (0.053)   
c.neg#c.ri~2        0.008*         -0.004          -0.017   
                  (0.004)         (0.005)         (0.012)   
order              -0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.006          -0.027***       -0.309***
                  (0.006)         (0.004)         (0.006)   
female             -0.001           0.004           0.009   
                  (0.005)         (0.004)         (0.009)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.025*          0.010           0.014   
                  (0.012)         (0.009)         (0.019)   
university          0.006          -0.003           0.004   
                  (0.005)         (0.006)         (0.009)   
_cons              -0.007           0.017          -0.079   
                  (0.019)         (0.017)         (0.041)   
------------------------------------------------------------
r2_w                0.005           0.010           0.143   
r2_b                0.290           0.103           0.016   
r2_o                0.007           0.011           0.136   
N                3888.000        6000.000       17631.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   
. * Table A6 Row 6
.   replace right2= wp_right2
(0 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010***        0.014**         0.013   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.013          -0.035           0.055   
                  (0.008)         (0.033)         (0.055)   
c.neg#c.ri~2       -0.002           0.000          -0.002   
                  (0.002)         (0.006)         (0.011)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.028***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.005           0.013   
                  (0.002)         (0.006)         (0.012)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006          -0.001          -0.048*  
                  (0.003)         (0.014)         (0.024)   
university          0.002          -0.001           0.040** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.020*         -0.032          -0.096   
                  (0.008)         (0.028)         (0.050)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.137           0.023   
r2_o                0.053           0.011           0.088   
N              138036.000        5607.000        4617.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.008           0.000   
                  (0.004)         (0.004)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.009          -0.032          -0.049** 
                  (0.028)         (0.034)         (0.017)   
c.neg#c.ri~2       -0.001           0.008           0.009** 
                  (0.005)         (0.006)         (0.003)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.005          -0.005          -0.004   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.002          -0.003   
                  (0.014)         (0.012)         (0.007)   
university         -0.003           0.010          -0.003   
                  (0.005)         (0.007)         (0.003)   
_cons              -0.003           0.010           0.006   
                  (0.024)         (0.026)         (0.012)   
------------------------------------------------------------
r2_w                0.011           0.008           0.009   
r2_b                0.096           0.240           0.004   
r2_o                0.011           0.009           0.008   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004           0.001          -0.003           0.001   
                  (0.004)         (0.003)         (0.003)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.053          -0.013          -0.009           0.035   
                  (0.032)         (0.016)         (0.018)         (0.030)   
c.neg#c.ri~2       -0.005           0.003           0.002          -0.002   
                  (0.006)         (0.003)         (0.003)         (0.005)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.053***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.005          -0.006*         -0.002           0.004   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.020           0.001          -0.011           0.003   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.014**        -0.001           0.004           0.001   
                  (0.005)         (0.002)         (0.004)         (0.008)   
_cons              -0.003           0.019           0.023          -0.021   
                  (0.026)         (0.014)         (0.018)         (0.031)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.010           0.021   
r2_b                0.105           0.082           0.000           0.009   
r2_o                0.012           0.008           0.010           0.020   
N                8721.000       10260.000        8199.000        4104.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.004           0.020***
                  (0.005)         (0.003)         (0.006)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.015          -0.012           0.020   
                  (0.036)         (0.028)         (0.047)   
c.neg#c.ri~2       -0.000           0.004          -0.004   
                  (0.007)         (0.005)         (0.009)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.003           0.000           0.004   
                  (0.008)         (0.005)         (0.008)   
age                 0.005*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.007           0.020           0.014   
                  (0.019)         (0.013)         (0.015)   
university         -0.003          -0.003          -0.026*  
                  (0.022)         (0.007)         (0.012)   
_cons              -0.111*         -0.016          -0.052   
                  (0.051)         (0.023)         (0.064)   
------------------------------------------------------------
r2_w                0.009           0.014           0.021   
r2_b                0.160           0.184           0.034   
r2_o                0.010           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.014***        0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.001           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.022           0.022          -0.002   
                  (0.028)         (0.024)         (0.008)   
c.neg#c.ri~2       -0.007          -0.001           0.001   
                  (0.005)         (0.005)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007** 
                  (0.005)         (0.005)         (0.003)   
female             -0.003           0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.014           0.011*  
                  (0.009)         (0.011)         (0.005)   
university          0.000          -0.004           0.002   
                  (0.006)         (0.007)         (0.002)   
_cons              -0.009          -0.006          -0.019*  
                  (0.023)         (0.025)         (0.008)   
------------------------------------------------------------
r2_w                0.029           0.016           0.002   
r2_b                0.023           0.044           0.193   
r2_o                0.027           0.016           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.004           0.020** 
                  (0.003)         (0.003)         (0.007)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.014           0.001           0.082   
                  (0.022)         (0.021)         (0.050)   
c.neg#c.ri~2        0.006          -0.003          -0.015   
                  (0.004)         (0.004)         (0.010)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.005           0.006           0.006   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.026           0.007           0.003   
                  (0.013)         (0.007)         (0.016)   
university          0.006          -0.005           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.012           0.010          -0.071   
                  (0.021)         (0.016)         (0.038)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.318           0.152           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   replace right2= wp_right2_dicho2
(430,722 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.014***        0.013   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.030   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.010**         0.000           0.040   
                  (0.004)         (0.013)         (0.030)   
c.neg#c.ri~2       -0.002*         -0.002          -0.001   
                  (0.001)         (0.002)         (0.006)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.028***       -0.187***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.004           0.011   
                  (0.002)         (0.007)         (0.012)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006          -0.002          -0.037   
                  (0.003)         (0.015)         (0.024)   
university          0.002          -0.003           0.037** 
                  (0.002)         (0.007)         (0.013)   
_cons              -0.019*         -0.044          -0.088   
                  (0.007)         (0.027)         (0.048)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.005           0.049           0.069   
r2_o                0.053           0.010           0.089   
N              138036.000        5607.000        4617.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010**         0.011**         0.002   
                  (0.004)         (0.003)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.007          -0.004          -0.022** 
                  (0.014)         (0.010)         (0.007)   
c.neg#c.ri~2       -0.002           0.002           0.004***
                  (0.003)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.004          -0.005          -0.004   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.011          -0.004          -0.003   
                  (0.014)         (0.012)         (0.007)   
university         -0.002           0.009          -0.003   
                  (0.005)         (0.006)         (0.003)   
_cons              -0.010          -0.002          -0.004   
                  (0.021)         (0.022)         (0.011)   
------------------------------------------------------------
r2_w                0.011           0.008           0.009   
r2_b                0.052           0.269           0.003   
r2_o                0.011           0.009           0.008   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003           0.002          -0.001           0.001   
                  (0.004)         (0.002)         (0.003)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.025          -0.008           0.004           0.014   
                  (0.015)         (0.009)         (0.008)         (0.014)   
c.neg#c.ri~2       -0.005           0.001          -0.001          -0.001   
                  (0.003)         (0.002)         (0.002)         (0.003)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.052***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.006          -0.006*         -0.002           0.005   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                 0.000           0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.024           0.001          -0.010          -0.000   
                  (0.014)         (0.005)         (0.008)         (0.011)   
university          0.015**        -0.000           0.005          -0.000   
                  (0.005)         (0.003)         (0.004)         (0.008)   
_cons               0.006           0.018           0.015          -0.003   
                  (0.024)         (0.013)         (0.015)         (0.027)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.010           0.021   
r2_b                0.057           0.092           0.001           0.007   
r2_o                0.011           0.008           0.010           0.020   
N                8721.000       10260.000        8199.000        4104.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011*          0.005           0.018***
                  (0.004)         (0.003)         (0.005)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.017          -0.012          -0.002   
                  (0.016)         (0.018)         (0.019)   
c.neg#c.ri~2       -0.002           0.003           0.002   
                  (0.003)         (0.003)         (0.004)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.002           0.000           0.005   
                  (0.008)         (0.005)         (0.007)   
age                 0.005*          0.001           0.003   
                  (0.002)         (0.000)         (0.002)   
income              0.007           0.020           0.015   
                  (0.019)         (0.013)         (0.015)   
university         -0.007          -0.002          -0.028*  
                  (0.022)         (0.008)         (0.012)   
_cons              -0.112*         -0.018          -0.055   
                  (0.048)         (0.022)         (0.057)   
------------------------------------------------------------
r2_w                0.009           0.015           0.021   
r2_b                0.184           0.179           0.042   
r2_o                0.011           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.015***        0.014***        0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.000           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.009           0.007          -0.003   
                  (0.013)         (0.012)         (0.003)   
c.neg#c.ri~2       -0.001           0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007** 
                  (0.005)         (0.005)         (0.003)   
female              0.000           0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.012          -0.016           0.012*  
                  (0.009)         (0.012)         (0.005)   
university         -0.002          -0.003           0.002   
                  (0.006)         (0.007)         (0.002)   
_cons              -0.005           0.000          -0.018** 
                  (0.021)         (0.023)         (0.007)   
------------------------------------------------------------
r2_w                0.028           0.016           0.003   
r2_b                0.011           0.026           0.192   
r2_o                0.026           0.016           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***        0.003           0.018** 
                  (0.003)         (0.003)         (0.006)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.012           0.012           0.060** 
                  (0.011)         (0.010)         (0.021)   
c.neg#c.ri~2        0.004          -0.002          -0.012** 
                  (0.002)         (0.002)         (0.004)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.302***
                  (0.005)         (0.004)         (0.005)   
female              0.004           0.006           0.005   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000*         -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.023           0.005           0.004   
                  (0.014)         (0.007)         (0.016)   
university          0.005          -0.006           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.017           0.011          -0.056   
                  (0.020)         (0.015)         (0.035)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.281           0.133           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   replace right2= wp_right2_dichox
(122,898 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.013**         0.012   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.001          -0.020          -0.002   
                  (0.004)         (0.012)         (0.024)   
c.neg#c.ri~2       -0.001           0.001           0.003   
                  (0.001)         (0.002)         (0.005)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.028***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.003           0.011   
                  (0.002)         (0.006)         (0.013)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006           0.002          -0.048*  
                  (0.003)         (0.013)         (0.024)   
university          0.002           0.000           0.040** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.016*         -0.033          -0.081   
                  (0.007)         (0.026)         (0.050)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.234           0.003   
r2_o                0.053           0.012           0.088   
N              138036.000        5607.000        4617.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010**         0.012***        0.002   
                  (0.004)         (0.003)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.002          -0.003          -0.010   
                  (0.011)         (0.009)         (0.006)   
c.neg#c.ri~2       -0.001           0.001           0.002   
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.022***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.004          -0.005          -0.005   
                  (0.005)         (0.005)         (0.004)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.019          -0.002          -0.003   
                  (0.014)         (0.012)         (0.007)   
university         -0.001           0.010          -0.003   
                  (0.005)         (0.006)         (0.003)   
_cons              -0.006          -0.006          -0.003   
                  (0.022)         (0.022)         (0.012)   
------------------------------------------------------------
r2_w                0.011           0.008           0.007   
r2_b                0.159           0.237           0.003   
r2_o                0.011           0.009           0.007   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003           0.002          -0.002           0.002   
                  (0.004)         (0.002)         (0.002)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.014          -0.004           0.001           0.023   
                  (0.011)         (0.006)         (0.007)         (0.012)   
c.neg#c.ri~2       -0.001           0.001          -0.000          -0.002   
                  (0.002)         (0.001)         (0.001)         (0.002)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.037***       -0.023***       -0.030***       -0.053***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.006          -0.006*         -0.002           0.000   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.024           0.001          -0.010           0.002   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.013*         -0.001           0.004           0.001   
                  (0.005)         (0.002)         (0.004)         (0.008)   
_cons               0.008           0.014           0.017          -0.021   
                  (0.024)         (0.011)         (0.015)         (0.028)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.010           0.021   
r2_b                0.092           0.092           0.000           0.045   
r2_o                0.011           0.008           0.010           0.021   
N                8721.000       10260.000        8199.000        4104.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.005           0.018***
                  (0.005)         (0.003)         (0.005)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.014           0.002           0.001   
                  (0.014)         (0.008)         (0.016)   
c.neg#c.ri~2       -0.000           0.001          -0.001   
                  (0.003)         (0.002)         (0.003)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.023***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female              0.001           0.001           0.003   
                  (0.008)         (0.005)         (0.008)   
age                 0.005*          0.001*          0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.007           0.019           0.013   
                  (0.018)         (0.013)         (0.015)   
university          0.003          -0.002          -0.025*  
                  (0.021)         (0.007)         (0.012)   
_cons              -0.129**        -0.024          -0.036   
                  (0.049)         (0.022)         (0.059)   
------------------------------------------------------------
r2_w                0.009           0.014           0.021   
r2_b                0.231           0.241           0.037   
r2_o                0.011           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***        0.014***        0.002   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.001           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.006           0.003          -0.002   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ri~2       -0.000          -0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007** 
                  (0.005)         (0.005)         (0.003)   
female             -0.004           0.003           0.001   
                  (0.005)         (0.004)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.013           0.012*  
                  (0.009)         (0.012)         (0.005)   
university          0.001          -0.005           0.001   
                  (0.006)         (0.007)         (0.002)   
_cons               0.000           0.001          -0.019** 
                  (0.022)         (0.022)         (0.006)   
------------------------------------------------------------
r2_w                0.028           0.016           0.002   
r2_b                0.003           0.000           0.183   
r2_o                0.027           0.015           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***        0.003           0.017** 
                  (0.003)         (0.003)         (0.006)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.002          -0.006           0.018   
                  (0.010)         (0.008)         (0.018)   
c.neg#c.ri~2        0.001           0.000          -0.004   
                  (0.002)         (0.001)         (0.003)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.034***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.004           0.006           0.005   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.029*          0.008           0.005   
                  (0.014)         (0.007)         (0.016)   
university          0.008          -0.006           0.005   
                  (0.006)         (0.005)         (0.008)   
_cons              -0.017           0.013          -0.051   
                  (0.020)         (0.016)         (0.035)   
------------------------------------------------------------
r2_w                0.007           0.014           0.139   
r2_b                0.328           0.160           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   replace right2= left_right2
(418,383 real changes made, 561 to missing)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.012**         0.014   
                  (0.001)         (0.004)         (0.009)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.006          -0.042           0.036   
                  (0.007)         (0.023)         (0.046)   
c.neg#c.ri~2       -0.001           0.004          -0.003   
                  (0.001)         (0.004)         (0.009)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.027***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.004           0.008   
                  (0.002)         (0.006)         (0.012)   
age                -0.000          -0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006           0.003          -0.049*  
                  (0.003)         (0.014)         (0.024)   
university          0.002          -0.001           0.041** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.018*         -0.018          -0.099   
                  (0.008)         (0.028)         (0.052)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.148           0.011   
r2_o                0.053           0.011           0.088   
N              137865.000        5607.000        4617.000   
N_g               807.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009*          0.008           0.000   
                  (0.004)         (0.005)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003          -0.026          -0.034** 
                  (0.024)         (0.028)         (0.013)   
c.neg#c.ri~2        0.001           0.006           0.006** 
                  (0.005)         (0.005)         (0.002)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.003          -0.004          -0.004   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.010          -0.001          -0.001   
                  (0.014)         (0.011)         (0.008)   
university         -0.001           0.010          -0.003   
                  (0.005)         (0.007)         (0.003)   
_cons              -0.008           0.011           0.007   
                  (0.023)         (0.029)         (0.013)   
------------------------------------------------------------
r2_w                0.011           0.008           0.008   
r2_b                0.050           0.236           0.007   
r2_o                0.011           0.009           0.007   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.002           0.003          -0.004           0.004   
                  (0.004)         (0.002)         (0.003)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.025          -0.000          -0.018           0.015   
                  (0.024)         (0.012)         (0.013)         (0.020)   
c.neg#c.ri~2        0.001          -0.001           0.004          -0.006   
                  (0.005)         (0.002)         (0.002)         (0.004)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.051***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.004          -0.006**        -0.002           0.002   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.022           0.002          -0.010          -0.002   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.017**        -0.002           0.004           0.000   
                  (0.005)         (0.003)         (0.004)         (0.008)   
_cons              -0.000           0.010           0.027          -0.000   
                  (0.026)         (0.013)         (0.016)         (0.027)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.011           0.021   
r2_b                0.139           0.098           0.001           0.000   
r2_o                0.012           0.008           0.010           0.020   
N                8721.000       10089.000        8199.000        4104.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013*          0.005           0.013   
                  (0.006)         (0.003)         (0.007)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.016           0.005          -0.044   
                  (0.031)         (0.019)         (0.050)   
c.neg#c.ri~2       -0.004           0.001           0.012   
                  (0.006)         (0.003)         (0.010)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.002           0.001           0.004   
                  (0.008)         (0.005)         (0.007)   
age                 0.004*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.004           0.019           0.014   
                  (0.019)         (0.013)         (0.014)   
university         -0.003          -0.002          -0.026*  
                  (0.022)         (0.007)         (0.012)   
_cons              -0.113*         -0.020          -0.029   
                  (0.052)         (0.023)         (0.061)   
------------------------------------------------------------
r2_w                0.009           0.014           0.022   
r2_b                0.145           0.193           0.036   
r2_o                0.010           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.015***        0.014**         0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.000           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.006           0.019          -0.010*  
                  (0.027)         (0.031)         (0.004)   
c.neg#c.ri~2       -0.001           0.000           0.002** 
                  (0.005)         (0.006)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007*  
                  (0.005)         (0.005)         (0.003)   
female             -0.001           0.001           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.013          -0.010           0.013*  
                  (0.009)         (0.012)         (0.005)   
university         -0.001          -0.003           0.001   
                  (0.005)         (0.007)         (0.002)   
_cons              -0.005          -0.003          -0.016*  
                  (0.024)         (0.025)         (0.006)   
------------------------------------------------------------
r2_w                0.028           0.016           0.003   
r2_b                0.021           0.028           0.183   
r2_o                0.026           0.016           0.006   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.004           0.019** 
                  (0.004)         (0.003)         (0.007)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.008           0.002           0.041   
                  (0.021)         (0.021)         (0.036)   
c.neg#c.ri~2        0.004          -0.002          -0.010   
                  (0.004)         (0.004)         (0.007)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.003           0.005           0.005   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000*         -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.031*          0.007           0.005   
                  (0.015)         (0.007)         (0.016)   
university          0.005          -0.006           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.011           0.012          -0.060   
                  (0.022)         (0.017)         (0.037)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.292           0.145           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   replace right2= left_right2_dichox
(397,743 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.008***        0.013**         0.013   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003          -0.022          -0.005   
                  (0.004)         (0.012)         (0.024)   
c.neg#c.ri~2        0.001           0.001           0.000   
                  (0.001)         (0.002)         (0.005)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.027***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.005           0.007   
                  (0.002)         (0.006)         (0.012)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006          -0.002          -0.046   
                  (0.003)         (0.012)         (0.024)   
university          0.002          -0.002           0.039** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.014          -0.027          -0.079   
                  (0.008)         (0.026)         (0.050)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.212           0.000   
r2_o                0.053           0.011           0.087   
N              137865.000        5607.000        4617.000   
N_g               807.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010**         0.012***        0.002   
                  (0.004)         (0.003)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.001          -0.002          -0.009   
                  (0.011)         (0.009)         (0.006)   
c.neg#c.ri~2       -0.000           0.000           0.001   
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.004          -0.004          -0.004   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.011          -0.001          -0.002   
                  (0.014)         (0.011)         (0.007)   
university         -0.001           0.010          -0.004   
                  (0.005)         (0.006)         (0.003)   
_cons              -0.009          -0.006          -0.004   
                  (0.022)         (0.022)         (0.011)   
------------------------------------------------------------
r2_w                0.011           0.008           0.007   
r2_b                0.049           0.237           0.009   
r2_o                0.011           0.009           0.007   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003           0.002          -0.003           0.003   
                  (0.004)         (0.002)         (0.002)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.011          -0.005          -0.011           0.010   
                  (0.011)         (0.006)         (0.007)         (0.011)   
c.neg#c.ri~2       -0.000           0.000           0.002          -0.004   
                  (0.002)         (0.001)         (0.001)         (0.002)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.051***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.005          -0.007**        -0.002           0.003   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                 0.000           0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.022           0.002          -0.011          -0.001   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.016**        -0.002           0.004           0.002   
                  (0.005)         (0.003)         (0.004)         (0.008)   
_cons               0.006           0.013           0.023          -0.001   
                  (0.024)         (0.011)         (0.015)         (0.025)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.011           0.022   
r2_b                0.094           0.108           0.001           0.005   
r2_o                0.011           0.009           0.010           0.021   
N                8721.000       10089.000        8199.000        4104.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.005*          0.015** 
                  (0.004)         (0.003)         (0.005)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.004           0.005          -0.022   
                  (0.014)         (0.008)         (0.015)   
c.neg#c.ri~2       -0.000          -0.000           0.006*  
                  (0.003)         (0.002)         (0.003)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.040***
                  (0.005)         (0.005)         (0.004)   
female             -0.003           0.001           0.002   
                  (0.008)         (0.005)         (0.008)   
age                 0.004*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.003           0.019           0.014   
                  (0.019)         (0.013)         (0.014)   
university         -0.001          -0.001          -0.027*  
                  (0.022)         (0.008)         (0.012)   
_cons              -0.097*         -0.023          -0.035   
                  (0.048)         (0.023)         (0.055)   
------------------------------------------------------------
r2_w                0.009           0.014           0.022   
r2_b                0.164           0.193           0.044   
r2_o                0.010           0.016           0.022   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***        0.012**         0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.000           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.008          -0.006          -0.010***
                  (0.011)         (0.012)         (0.003)   
c.neg#c.ri~2        0.001           0.002           0.002***
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.024***        0.006*  
                  (0.005)         (0.005)         (0.003)   
female             -0.004           0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.012          -0.012           0.013*  
                  (0.009)         (0.012)         (0.005)   
university         -0.001          -0.004           0.001   
                  (0.005)         (0.007)         (0.002)   
_cons               0.003           0.008          -0.015*  
                  (0.022)         (0.023)         (0.006)   
------------------------------------------------------------
r2_w                0.028           0.016           0.004   
r2_b                0.008           0.002           0.185   
r2_o                0.027           0.015           0.006   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.003           0.015*  
                  (0.003)         (0.003)         (0.006)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003          -0.004          -0.000   
                  (0.010)         (0.008)         (0.018)   
c.neg#c.ri~2        0.003          -0.000           0.000   
                  (0.002)         (0.001)         (0.003)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.004           0.004           0.005   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000*         -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.032*          0.008           0.004   
                  (0.014)         (0.007)         (0.016)   
university          0.006          -0.007           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.013           0.016          -0.043   
                  (0.020)         (0.016)         (0.036)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.350           0.186           0.000   
r2_o                0.011           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   replace right2= ideo_right2
(444,626 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010***        0.012**         0.014   
                  (0.001)         (0.005)         (0.009)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.013          -0.052           0.048   
                  (0.009)         (0.030)         (0.053)   
c.neg#c.ri~2       -0.002           0.003          -0.003   
                  (0.002)         (0.006)         (0.010)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.027***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.005           0.010   
                  (0.002)         (0.006)         (0.012)   
age                -0.000          -0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006           0.003          -0.049*  
                  (0.003)         (0.013)         (0.024)   
university          0.002          -0.000           0.041** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.021*         -0.020          -0.100   
                  (0.008)         (0.028)         (0.051)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.182           0.018   
r2_o                0.053           0.011           0.088   
N              137865.000        5607.000        4617.000   
N_g               807.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.005          -0.000   
                  (0.004)         (0.006)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.007          -0.050          -0.046** 
                  (0.030)         (0.041)         (0.016)   
c.neg#c.ri~2        0.000           0.012           0.008** 
                  (0.006)         (0.008)         (0.003)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.005          -0.004          -0.005   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.012          -0.002          -0.002   
                  (0.014)         (0.012)         (0.008)   
university         -0.002           0.010          -0.003   
                  (0.005)         (0.007)         (0.003)   
_cons              -0.006           0.023           0.009   
                  (0.024)         (0.031)         (0.013)   
------------------------------------------------------------
r2_w                0.011           0.008           0.009   
r2_b                0.057           0.237           0.007   
r2_o                0.011           0.009           0.008   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003           0.003          -0.006           0.005   
                  (0.004)         (0.003)         (0.003)         (0.005)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.042          -0.012          -0.028           0.036   
                  (0.030)         (0.023)         (0.021)         (0.033)   
c.neg#c.ri~2       -0.002           0.000           0.007          -0.008   
                  (0.006)         (0.004)         (0.004)         (0.006)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.052***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.005          -0.006**        -0.002           0.003   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.021           0.002          -0.010          -0.003   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.016**        -0.002           0.005          -0.001   
                  (0.005)         (0.003)         (0.004)         (0.008)   
_cons              -0.004           0.017           0.034          -0.005   
                  (0.026)         (0.018)         (0.019)         (0.030)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.011           0.021   
r2_b                0.134           0.098           0.001           0.030   
r2_o                0.012           0.008           0.010           0.020   
N                8721.000       10089.000        8199.000        4104.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.020*          0.005           0.016*  
                  (0.010)         (0.003)         (0.007)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.111          -0.000          -0.013   
                  (0.088)         (0.024)         (0.058)   
c.neg#c.ri~2       -0.018           0.002           0.004   
                  (0.016)         (0.005)         (0.011)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.001           0.001           0.004   
                  (0.008)         (0.005)         (0.007)   
age                 0.004*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.006           0.019           0.015   
                  (0.019)         (0.013)         (0.015)   
university         -0.006          -0.002          -0.026*  
                  (0.022)         (0.007)         (0.012)   
_cons              -0.160*         -0.018          -0.045   
                  (0.068)         (0.023)         (0.066)   
------------------------------------------------------------
r2_w                0.009           0.014           0.021   
r2_b                0.154           0.191           0.035   
r2_o                0.011           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.014**         0.000   
                  (0.004)         (0.005)         (0.001)   
timesecSto~g       -0.000           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.016           0.036          -0.015*  
                  (0.030)         (0.035)         (0.007)   
c.neg#c.ri~2       -0.005          -0.001           0.003** 
                  (0.006)         (0.007)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007*  
                  (0.005)         (0.005)         (0.003)   
female             -0.002           0.000           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.013          -0.011           0.012*  
                  (0.009)         (0.011)         (0.005)   
university         -0.000          -0.003           0.001   
                  (0.006)         (0.007)         (0.002)   
_cons              -0.008          -0.010          -0.012   
                  (0.024)         (0.027)         (0.007)   
------------------------------------------------------------
r2_w                0.028           0.016           0.003   
r2_b                0.021           0.083           0.182   
r2_o                0.027           0.016           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012***        0.004           0.020** 
                  (0.004)         (0.003)         (0.007)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.013           0.002           0.065   
                  (0.023)         (0.023)         (0.045)   
c.neg#c.ri~2        0.006          -0.003          -0.014   
                  (0.004)         (0.004)         (0.009)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.004           0.005           0.005   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.029*          0.008           0.004   
                  (0.014)         (0.007)         (0.016)   
university          0.006          -0.005           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.010           0.011          -0.067   
                  (0.021)         (0.017)         (0.038)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.311           0.153           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   replace right2= ideo_right2_dichox
(444,626 real changes made)
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.013**         0.013   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.002          -0.023*         -0.002   
                  (0.004)         (0.012)         (0.023)   
c.neg#c.ri~2       -0.000           0.002          -0.001   
                  (0.001)         (0.002)         (0.005)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.027***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.006           0.006   
                  (0.002)         (0.005)         (0.012)   
age                -0.000          -0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006          -0.006          -0.047   
                  (0.003)         (0.012)         (0.024)   
university          0.002           0.001           0.040** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.016*         -0.026          -0.083   
                  (0.008)         (0.026)         (0.050)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.225           0.000   
r2_o                0.053           0.012           0.087   
N              137865.000        5607.000        4617.000   
N_g               807.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010**         0.011***        0.003   
                  (0.004)         (0.003)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.000          -0.006          -0.009   
                  (0.011)         (0.009)         (0.006)   
c.neg#c.ri~2       -0.000           0.002           0.001   
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.004          -0.005          -0.005   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.012          -0.004          -0.002   
                  (0.015)         (0.012)         (0.008)   
university         -0.001           0.010          -0.003   
                  (0.005)         (0.006)         (0.003)   
_cons              -0.009          -0.005          -0.005   
                  (0.022)         (0.022)         (0.012)   
------------------------------------------------------------
r2_w                0.011           0.008           0.007   
r2_b                0.051           0.266           0.010   
r2_o                0.011           0.009           0.007   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.003           0.003          -0.003           0.002   
                  (0.004)         (0.002)         (0.002)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.002           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.014          -0.002          -0.010           0.009   
                  (0.011)         (0.005)         (0.007)         (0.012)   
c.neg#c.ri~2       -0.001          -0.000           0.002          -0.002   
                  (0.002)         (0.001)         (0.001)         (0.002)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.052***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.005          -0.006**        -0.002           0.004   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                 0.000           0.000           0.000           0.000   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.021           0.001          -0.010          -0.003   
                  (0.013)         (0.005)         (0.009)         (0.011)   
university          0.015**        -0.001           0.005          -0.000   
                  (0.005)         (0.002)         (0.004)         (0.008)   
_cons               0.005           0.011           0.023           0.003   
                  (0.024)         (0.011)         (0.015)         (0.027)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.011           0.021   
r2_b                0.091           0.110           0.001           0.036   
r2_o                0.011           0.009           0.010           0.020   
N                8721.000       10089.000        8199.000        4104.000   
N_g                51.000          59.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013**         0.006*          0.016** 
                  (0.005)         (0.003)         (0.005)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.023           0.006          -0.015   
                  (0.014)         (0.008)         (0.015)   
c.neg#c.ri~2       -0.005          -0.000           0.004   
                  (0.003)         (0.002)         (0.003)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.002           0.001           0.004   
                  (0.008)         (0.005)         (0.007)   
age                 0.004*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.004           0.020           0.015   
                  (0.019)         (0.013)         (0.015)   
university         -0.004          -0.001          -0.026*  
                  (0.022)         (0.008)         (0.012)   
_cons              -0.111*         -0.024          -0.043   
                  (0.049)         (0.023)         (0.057)   
------------------------------------------------------------
r2_w                0.010           0.014           0.022   
r2_b                0.143           0.194           0.037   
r2_o                0.011           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014***        0.014***        0.002   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.000           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003           0.005          -0.005   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ri~2        0.001          -0.001           0.001   
                  (0.002)         (0.002)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007*  
                  (0.005)         (0.005)         (0.003)   
female             -0.001           0.003           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.013          -0.013           0.013*  
                  (0.009)         (0.012)         (0.005)   
university         -0.001          -0.004           0.001   
                  (0.005)         (0.007)         (0.002)   
_cons              -0.001           0.001          -0.018** 
                  (0.022)         (0.022)         (0.006)   
------------------------------------------------------------
r2_w                0.028           0.016           0.003   
r2_b                0.020           0.000           0.183   
r2_o                0.026           0.015           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.003           0.016*  
                  (0.003)         (0.003)         (0.006)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.003          -0.002           0.008   
                  (0.010)         (0.008)         (0.018)   
c.neg#c.ri~2        0.003          -0.001          -0.001   
                  (0.002)         (0.001)         (0.003)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.004           0.005           0.005   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.032*          0.008           0.004   
                  (0.014)         (0.007)         (0.016)   
university          0.006          -0.006           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.013           0.013          -0.047   
                  (0.020)         (0.016)         (0.035)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.350           0.194           0.000   
r2_o                0.011           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
. * Table A8 Row 6
.   replace right2= wp_right2
(431,283 real changes made)
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; wp_right2_ext==1, re   
.   estimates store B 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; political_interest_dichox==1, r
&gt; e   
.   estimates store C
.   esttab  A B C , cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010***        0.009***        0.012***
                  (0.001)         (0.002)         (0.002)   
timesecSto~g        0.002           0.004           0.012*  
                  (0.004)         (0.005)         (0.005)   
c.neg#c.ti~g       -0.004***       -0.004***       -0.006***
                  (0.001)         (0.001)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.013           0.007           0.014   
                  (0.008)         (0.009)         (0.011)   
c.neg#c.ri~2       -0.002          -0.001          -0.002   
                  (0.002)         (0.002)         (0.002)   
order               0.000*          0.000*          0.000** 
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.131***       -0.129***       -0.132***
                  (0.002)         (0.002)         (0.002)   
female              0.003           0.001           0.003   
                  (0.002)         (0.002)         (0.002)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.006          -0.005          -0.009   
                  (0.003)         (0.004)         (0.005)   
university          0.002           0.003           0.005   
                  (0.002)         (0.002)         (0.003)   
_cons              -0.020*         -0.019          -0.039***
                  (0.008)         (0.010)         (0.012)   
------------------------------------------------------------
r2_w                0.055           0.054           0.057   
r2_b                0.006           0.029           0.017   
r2_o                0.053           0.052           0.054   
N              138036.000       74334.000       64760.000   
N_g               808.000         435.000         379.000   
------------------------------------------------------------
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 , re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 , re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010***        0.014**         0.013   
                  (0.001)         (0.004)         (0.008)   
timesecSto~g        0.002           0.026*          0.031   
                  (0.004)         (0.011)         (0.023)   
c.neg#c.ti~g       -0.004***       -0.009***       -0.006   
                  (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.013          -0.035           0.055   
                  (0.008)         (0.033)         (0.055)   
c.neg#c.ri~2       -0.002           0.000          -0.002   
                  (0.002)         (0.006)         (0.011)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.131***       -0.028***       -0.186***
                  (0.002)         (0.005)         (0.009)   
female              0.003           0.005           0.013   
                  (0.002)         (0.006)         (0.012)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.006          -0.001          -0.048*  
                  (0.003)         (0.014)         (0.024)   
university          0.002          -0.001           0.040** 
                  (0.002)         (0.006)         (0.013)   
_cons              -0.020*         -0.032          -0.096   
                  (0.008)         (0.028)         (0.050)   
------------------------------------------------------------
r2_w                0.055           0.010           0.092   
r2_b                0.006           0.137           0.023   
r2_o                0.053           0.011           0.088   
N              138036.000        5607.000        4617.000   
N_g               808.000          33.000          27.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.008           0.000   
                  (0.004)         (0.004)         (0.002)   
timesecSto~g       -0.001           0.011          -0.001   
                  (0.011)         (0.009)         (0.005)   
c.neg#c.ti~g       -0.005**        -0.006***       -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.009          -0.032          -0.049** 
                  (0.028)         (0.034)         (0.017)   
c.neg#c.ri~2       -0.001           0.008           0.009** 
                  (0.005)         (0.006)         (0.003)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.021***       -0.021***       -0.018***
                  (0.004)         (0.003)         (0.004)   
female              0.005          -0.005          -0.004   
                  (0.005)         (0.004)         (0.003)   
age                 0.000          -0.001*          0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.002          -0.003   
                  (0.014)         (0.012)         (0.007)   
university         -0.003           0.010          -0.003   
                  (0.005)         (0.007)         (0.003)   
_cons              -0.003           0.010           0.006   
                  (0.024)         (0.026)         (0.012)   
------------------------------------------------------------
r2_w                0.011           0.008           0.009   
r2_b                0.096           0.240           0.004   
r2_o                0.011           0.009           0.008   
N                6156.000        9747.000        5985.000   
N_g                36.000          57.000          35.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 , re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 , re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.004           0.001          -0.003           0.001   
                  (0.004)         (0.003)         (0.003)         (0.004)   
timesecSto~g       -0.015          -0.005          -0.016*         -0.010   
                  (0.011)         (0.005)         (0.007)         (0.011)   
c.neg#c.ti~g       -0.000          -0.001           0.001          -0.000   
                  (0.002)         (0.001)         (0.001)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.053          -0.013          -0.009           0.035   
                  (0.032)         (0.016)         (0.018)         (0.030)   
c.neg#c.ri~2       -0.005           0.003           0.002          -0.002   
                  (0.006)         (0.003)         (0.003)         (0.005)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.038***       -0.023***       -0.030***       -0.053***
                  (0.004)         (0.003)         (0.004)         (0.006)   
female              0.005          -0.006*         -0.002           0.004   
                  (0.005)         (0.002)         (0.004)         (0.006)   
age                -0.000           0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.000)         (0.001)   
income             -0.020           0.001          -0.011           0.003   
                  (0.013)         (0.005)         (0.008)         (0.011)   
university          0.014**        -0.001           0.004           0.001   
                  (0.005)         (0.002)         (0.004)         (0.008)   
_cons              -0.003           0.019           0.023          -0.021   
                  (0.026)         (0.014)         (0.018)         (0.031)   
----------------------------------------------------------------------------
r2_w                0.011           0.008           0.010           0.021   
r2_b                0.105           0.082           0.000           0.009   
r2_o                0.012           0.008           0.010           0.020   
N                8721.000       10260.000        8199.000        4104.000   
N_g                51.000          60.000          48.000          24.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.004           0.020***
                  (0.005)         (0.003)         (0.006)   
timesecSto~g        0.009          -0.004           0.001   
                  (0.013)         (0.008)         (0.015)   
c.neg#c.ti~g       -0.007**        -0.004*         -0.009** 
                  (0.002)         (0.002)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.015          -0.012           0.020   
                  (0.036)         (0.028)         (0.047)   
c.neg#c.ri~2       -0.000           0.004          -0.004   
                  (0.007)         (0.005)         (0.009)   
order               0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.024***       -0.033***       -0.039***
                  (0.005)         (0.005)         (0.004)   
female             -0.003           0.000           0.004   
                  (0.008)         (0.005)         (0.008)   
age                 0.005*          0.001           0.002   
                  (0.002)         (0.000)         (0.002)   
income              0.007           0.020           0.014   
                  (0.019)         (0.013)         (0.015)   
university         -0.003          -0.003          -0.026*  
                  (0.022)         (0.007)         (0.012)   
_cons              -0.111*         -0.016          -0.052   
                  (0.051)         (0.023)         (0.064)   
------------------------------------------------------------
r2_w                0.009           0.014           0.021   
r2_b                0.160           0.184           0.034   
r2_o                0.010           0.016           0.021   
N                5472.000        6327.000        6154.000   
N_g                32.000          37.000          36.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 , re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 , re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 , re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 , re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 , re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 , re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.016***        0.014***        0.001   
                  (0.004)         (0.004)         (0.001)   
timesecSto~g       -0.001           0.010           0.003   
                  (0.011)         (0.010)         (0.003)   
c.neg#c.ti~g       -0.007**        -0.008***       -0.001*  
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.022           0.022          -0.002   
                  (0.028)         (0.024)         (0.008)   
c.neg#c.ri~2       -0.007          -0.001           0.001   
                  (0.005)         (0.005)         (0.001)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.025***        0.007** 
                  (0.005)         (0.005)         (0.003)   
female             -0.003           0.002           0.001   
                  (0.006)         (0.005)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.015          -0.014           0.011*  
                  (0.009)         (0.011)         (0.005)   
university          0.000          -0.004           0.002   
                  (0.006)         (0.007)         (0.002)   
_cons              -0.009          -0.006          -0.019*  
                  (0.023)         (0.025)         (0.008)   
------------------------------------------------------------
r2_w                0.029           0.016           0.002   
r2_b                0.023           0.044           0.193   
r2_o                0.027           0.016           0.005   
N                5472.000        5472.000        8208.000   
N_g                32.000          32.000          48.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013***        0.004           0.020** 
                  (0.003)         (0.003)         (0.007)   
timesecSto~g        0.022*         -0.008           0.016   
                  (0.009)         (0.007)         (0.017)   
c.neg#c.ti~g       -0.008***       -0.001          -0.007*  
                  (0.002)         (0.001)         (0.003)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.014           0.001           0.082   
                  (0.022)         (0.021)         (0.050)   
c.neg#c.ri~2        0.006          -0.003          -0.015   
                  (0.004)         (0.004)         (0.010)   
order              -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.008          -0.035***       -0.301***
                  (0.005)         (0.004)         (0.005)   
female              0.005           0.006           0.006   
                  (0.005)         (0.004)         (0.008)   
age                -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.026           0.007           0.003   
                  (0.013)         (0.007)         (0.016)   
university          0.006          -0.005           0.005   
                  (0.005)         (0.005)         (0.008)   
_cons              -0.012           0.010          -0.071   
                  (0.021)         (0.016)         (0.038)   
------------------------------------------------------------
r2_w                0.008           0.014           0.139   
r2_b                0.318           0.152           0.000   
r2_o                0.010           0.015           0.135   
N                5274.000        8160.000       23930.000   
N_g                31.000          48.000         140.000   
------------------------------------------------------------
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; wp_right2_ext==1, re  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; wp_right2_ex
&gt; t==1, re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.009***        0.006           0.004   
                  (0.002)         (0.006)         (0.013)   
timesecSto~g        0.004           0.017           0.032   
                  (0.005)         (0.015)         (0.037)   
c.neg#c.ti~g       -0.004***       -0.005           0.000   
                  (0.001)         (0.003)         (0.007)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.007          -0.033           0.052   
                  (0.009)         (0.035)         (0.072)   
c.neg#c.ri~2       -0.001           0.001          -0.002   
                  (0.002)         (0.006)         (0.014)   
order               0.000*          0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.129***       -0.003          -0.235***
                  (0.002)         (0.007)         (0.013)   
female              0.001           0.010          -0.005   
                  (0.002)         (0.013)         (0.022)   
age                -0.000           0.000          -0.000   
                  (0.000)         (0.001)         (0.001)   
income             -0.005           0.014          -0.077*  
                  (0.004)         (0.025)         (0.039)   
university          0.003          -0.019*          0.055** 
                  (0.002)         (0.009)         (0.019)   
_cons              -0.019          -0.020          -0.093   
                  (0.010)         (0.042)         (0.080)   
------------------------------------------------------------
r2_w                0.054           0.003           0.116   
r2_b                0.029           0.476           0.078   
r2_o                0.052           0.007           0.111   
N               74334.000        2718.000        2736.000   
N_g               435.000          16.000          16.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.013**         0.008          -0.001   
                  (0.005)         (0.005)         (0.003)   
timesecSto~g        0.005           0.013          -0.003   
                  (0.012)         (0.010)         (0.007)   
c.neg#c.ti~g       -0.007**        -0.007**        -0.001   
                  (0.002)         (0.002)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.007          -0.031          -0.066** 
                  (0.026)         (0.035)         (0.020)   
c.neg#c.ri~2       -0.000           0.008           0.012***
                  (0.005)         (0.006)         (0.003)   
order               0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.028***       -0.019***       -0.033***
                  (0.006)         (0.004)         (0.006)   
female             -0.005          -0.006          -0.006   
                  (0.007)         (0.006)         (0.006)   
age                -0.000          -0.001*          0.000   
                  (0.000)         (0.001)         (0.000)   
income              0.002           0.003          -0.003   
                  (0.017)         (0.014)         (0.012)   
university          0.005           0.008          -0.007   
                  (0.007)         (0.009)         (0.006)   
_cons              -0.020           0.014           0.017   
                  (0.029)         (0.029)         (0.019)   
------------------------------------------------------------
r2_w                0.017           0.007           0.017   
r2_b                0.172           0.231           0.207   
r2_o                0.017           0.008           0.019   
N                3249.000        7353.000        3078.000   
N_g                19.000          43.000          18.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; wp_right2_ex
&gt; t==1, re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; wp_right2_ex
&gt; t==1, re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                 0.007           0.003          -0.004          -0.003   
                  (0.005)         (0.003)         (0.005)         (0.003)   
timesecSto~g       -0.005           0.005          -0.026*         -0.005   
                  (0.014)         (0.006)         (0.011)         (0.008)   
c.neg#c.ti~g       -0.002          -0.003*          0.002           0.000   
                  (0.003)         (0.001)         (0.002)         (0.002)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.039          -0.013          -0.011          -0.034   
                  (0.031)         (0.015)         (0.023)         (0.028)   
c.neg#c.ri~2       -0.007           0.003           0.003           0.006   
                  (0.006)         (0.003)         (0.004)         (0.004)   
order               0.000          -0.000          -0.000          -0.000   
                  (0.000)         (0.000)         (0.000)         (0.000)   
L.gslmc            -0.039***       -0.013**        -0.034***       -0.022***
                  (0.006)         (0.004)         (0.005)         (0.006)   
female              0.004          -0.006          -0.004           0.002   
                  (0.007)         (0.003)         (0.006)         (0.006)   
age                 0.000           0.000           0.000          -0.000   
                  (0.000)         (0.000)         (0.001)         (0.001)   
income             -0.035          -0.002          -0.010          -0.009   
                  (0.018)         (0.005)         (0.017)         (0.014)   
university          0.017*         -0.004           0.004          -0.008   
                  (0.007)         (0.004)         (0.008)         (0.008)   
_cons              -0.017          -0.002           0.032           0.044   
                  (0.030)         (0.015)         (0.029)         (0.038)   
----------------------------------------------------------------------------
r2_w                0.013           0.004           0.013           0.009   
r2_b                0.268           0.198           0.002           0.097   
r2_o                0.015           0.005           0.012           0.010   
N                3933.000        5643.000        4608.000        2394.000   
N_g                23.000          33.000          27.000          14.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.005           0.004           0.024** 
                  (0.007)         (0.004)         (0.008)   
timesecSto~g       -0.006          -0.004           0.009   
                  (0.019)         (0.011)         (0.021)   
c.neg#c.ti~g       -0.005          -0.003          -0.012** 
                  (0.004)         (0.002)         (0.004)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.012          -0.030           0.040   
                  (0.043)         (0.031)         (0.050)   
c.neg#c.ri~2       -0.002           0.005          -0.003   
                  (0.007)         (0.006)         (0.009)   
order               0.000          -0.000           0.000   
                  (0.001)         (0.000)         (0.001)   
L.gslmc            -0.034***       -0.041***       -0.057***
                  (0.007)         (0.007)         (0.006)   
female             -0.004          -0.003           0.010   
                  (0.014)         (0.007)         (0.010)   
age                 0.005          -0.000           0.007*  
                  (0.007)         (0.002)         (0.004)   
income             -0.012           0.025           0.005   
                  (0.048)         (0.018)         (0.017)   
university         -0.082          -0.007          -0.019   
                  (0.154)         (0.016)         (0.025)   
_cons               0.000           0.014          -0.191*  
                      (.)         (0.053)         (0.085)   
------------------------------------------------------------
r2_w                0.013           0.017           0.036   
r2_b                0.032           0.260           0.333   
r2_o                0.013           0.019           0.038   
N                2736.000        3249.000        2907.000   
N_g                16.000          19.000          17.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; wp_right2_ext=
&gt; =1, re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.026***        0.022***        0.000   
                  (0.006)         (0.007)         (0.002)   
timesecSto~g        0.012           0.024           0.004   
                  (0.016)         (0.017)         (0.004)   
c.neg#c.ti~g       -0.011***       -0.013***       -0.001   
                  (0.003)         (0.003)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.046           0.034          -0.004   
                  (0.035)         (0.030)         (0.010)   
c.neg#c.ri~2       -0.011          -0.002           0.002   
                  (0.006)         (0.006)         (0.002)   
order              -0.001           0.000           0.000   
                  (0.000)         (0.001)         (0.000)   
L.gslmc            -0.050***       -0.036***        0.009*  
                  (0.007)         (0.008)         (0.004)   
female             -0.004          -0.006          -0.001   
                  (0.009)         (0.008)         (0.003)   
age                 0.000          -0.001           0.000   
                  (0.000)         (0.000)         (0.000)   
income              0.000          -0.024           0.011   
                  (0.016)         (0.017)         (0.007)   
university         -0.017          -0.027           0.000   
                  (0.011)         (0.036)         (0.003)   
_cons              -0.038           0.000          -0.014   
                  (0.033)             (.)         (0.012)   
------------------------------------------------------------
r2_w                0.035           0.021           0.002   
r2_b                0.022           0.173           0.190   
r2_o                0.034           0.021           0.003   
N                3249.000        2907.000        4275.000   
N_g                19.000          17.000          25.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.010*          0.003           0.018*  
                  (0.004)         (0.003)         (0.009)   
timesecSto~g        0.011          -0.006           0.024   
                  (0.012)         (0.008)         (0.023)   
c.neg#c.ti~g       -0.006*         -0.000          -0.009*  
                  (0.002)         (0.002)         (0.004)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.005           0.001           0.076   
                  (0.025)         (0.018)         (0.050)   
c.neg#c.ri~2        0.006          -0.002          -0.012   
                  (0.004)         (0.003)         (0.010)   
order              -0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc             0.041***       -0.034***       -0.305***
                  (0.006)         (0.005)         (0.007)   
female              0.004           0.004           0.009   
                  (0.015)         (0.005)         (0.010)   
age                -0.000          -0.000          -0.001   
                  (0.000)         (0.000)         (0.000)   
income             -0.031           0.007           0.006   
                  (0.025)         (0.012)         (0.021)   
university          0.012          -0.005           0.017   
                  (0.010)         (0.006)         (0.011)   
_cons               0.005           0.008          -0.077   
                  (0.036)         (0.018)         (0.048)   
------------------------------------------------------------
r2_w                0.023           0.013           0.141   
r2_b                0.522           0.235           0.067   
r2_o                0.031           0.015           0.136   
N                2556.000        4095.000       12648.000   
N_g                15.000          24.000          74.000   
------------------------------------------------------------
.   
.   xtset resp timesec
       panel variable:  resp (unbalanced)
        time variable:  timesec, 1 to 565
                delta:  1 unit
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if period==2 &amp; political_interest_dichox==1, r
&gt; e  
.   estimates store G
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;BR&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CA.f&quot; &amp; period==2 &amp; political_in
&gt; terest_dichox==1, re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CH&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;CN&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;DK&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store F 
.   esttab G A C, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.012***        0.009           0.016   
                  (0.002)         (0.006)         (0.009)   
timesecSto~g        0.012*          0.020           0.032   
                  (0.005)         (0.017)         (0.024)   
c.neg#c.ti~g       -0.006***       -0.007*         -0.007   
                  (0.001)         (0.003)         (0.005)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.014          -0.034           0.063   
                  (0.011)         (0.049)         (0.058)   
c.neg#c.ri~2       -0.002           0.000          -0.001   
                  (0.002)         (0.008)         (0.011)   
order               0.000**         0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.132***       -0.025***       -0.175***
                  (0.002)         (0.007)         (0.009)   
female              0.003          -0.004           0.016   
                  (0.002)         (0.012)         (0.013)   
age                -0.000          -0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.009           0.008          -0.047   
                  (0.005)         (0.026)         (0.025)   
university          0.005          -0.015           0.032*  
                  (0.003)         (0.013)         (0.013)   
_cons              -0.039***        0.010          -0.095   
                  (0.012)         (0.044)         (0.051)   
------------------------------------------------------------
r2_w                0.057           0.009           0.087   
r2_b                0.017           0.223           0.027   
r2_o                0.054           0.011           0.083   
N               64760.000        3069.000        4275.000   
N_g               379.000          18.000          25.000   
------------------------------------------------------------
.   esttab D E F, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.014           0.005           0.006   
                  (0.007)         (0.005)         (0.003)   
timesecSto~g        0.002           0.014           0.006   
                  (0.019)         (0.010)         (0.008)   
c.neg#c.ti~g       -0.006          -0.006***       -0.004*  
                  (0.004)         (0.002)         (0.002)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.003          -0.060          -0.057*  
                  (0.047)         (0.037)         (0.023)   
c.neg#c.ri~2       -0.001           0.016*          0.012** 
                  (0.009)         (0.007)         (0.004)   
order               0.000          -0.000           0.000   
                  (0.001)         (0.000)         (0.000)   
L.gslmc            -0.028***       -0.032***       -0.035***
                  (0.007)         (0.004)         (0.007)   
female             -0.002          -0.006           0.001   
                  (0.011)         (0.006)         (0.006)   
age                 0.001          -0.001          -0.000   
                  (0.000)         (0.001)         (0.000)   
income             -0.064          -0.001          -0.000   
                  (0.037)         (0.014)         (0.009)   
university         -0.005           0.007          -0.002   
                  (0.013)         (0.007)         (0.005)   
_cons              -0.020           0.010          -0.008   
                  (0.043)         (0.030)         (0.018)   
------------------------------------------------------------
r2_w                0.013           0.013           0.020   
r2_b                0.299           0.194           0.140   
r2_o                0.014           0.014           0.021   
N                2565.000        7011.000        2736.000   
N_g                15.000          41.000          16.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;FR&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store A
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;GH&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IN&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.j&quot; &amp; period==2 &amp; political_in
&gt; terest_dichox==1, re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IS.p&quot; &amp; period==2 &amp; political_in
&gt; terest_dichox==1, re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;IT&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;JP&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store G
.   esttab A B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b 
&gt; r2_o N N_g) 

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                  D.gslmc         D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se            b/se   
----------------------------------------------------------------------------
neg                -0.002           0.001          -0.004           0.016   
                  (0.007)         (0.003)         (0.005)         (0.009)   
timesecSto~g       -0.016          -0.005          -0.019           0.028   
                  (0.017)         (0.006)         (0.011)         (0.025)   
c.neg#c.ti~g        0.002          -0.001           0.002          -0.008   
                  (0.003)         (0.001)         (0.002)         (0.005)   
neg                 0.000           0.000           0.000           0.000   
                      (.)             (.)             (.)             (.)   
right2              0.075          -0.009          -0.023           0.032   
                  (0.053)         (0.018)         (0.027)         (0.077)   
c.neg#c.ri~2       -0.001           0.001           0.001          -0.006   
                  (0.009)         (0.003)         (0.005)         (0.014)   
order              -0.000           0.000          -0.000          -0.000   
                  (0.001)         (0.000)         (0.000)         (0.001)   
L.gslmc            -0.013           0.010*         -0.043***       -0.072***
                  (0.007)         (0.004)         (0.005)         (0.011)   
female             -0.003          -0.004           0.005           0.015   
                  (0.011)         (0.004)         (0.008)         (0.021)   
age                -0.001           0.000           0.000           0.000   
                  (0.001)         (0.000)         (0.000)         (0.001)   
income             -0.012          -0.001          -0.013           0.008   
                  (0.021)         (0.007)         (0.014)         (0.022)   
university          0.009          -0.001           0.010          -0.076   
                  (0.011)         (0.004)         (0.007)         (0.059)   
_cons               0.028           0.008           0.034           0.000   
                  (0.040)         (0.020)         (0.029)             (.)   
----------------------------------------------------------------------------
r2_w                0.002           0.004           0.016           0.031   
r2_b                0.281           0.029           0.009           0.323   
r2_o                0.006           0.004           0.016           0.031   
N                3078.000        4788.000        4275.000        1539.000   
N_g                18.000          28.000          25.000           9.000   
----------------------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.011           0.006           0.033***
                  (0.007)         (0.005)         (0.008)   
timesecSto~g        0.019           0.014           0.024   
                  (0.017)         (0.013)         (0.021)   
c.neg#c.ti~g       -0.009**        -0.005          -0.015***
                  (0.003)         (0.003)         (0.004)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.015           0.031           0.059   
                  (0.056)         (0.050)         (0.064)   
c.neg#c.ri~2        0.005           0.001          -0.014   
                  (0.011)         (0.009)         (0.011)   
order               0.001           0.000          -0.000   
                  (0.001)         (0.000)         (0.001)   
L.gslmc            -0.017**        -0.018*         -0.050***
                  (0.006)         (0.008)         (0.006)   
female             -0.012           0.013           0.032*  
                  (0.010)         (0.008)         (0.015)   
age                 0.004           0.001*          0.005   
                  (0.002)         (0.001)         (0.004)   
income              0.014          -0.013           0.039   
                  (0.025)         (0.024)         (0.029)   
university         -0.113*         -0.002          -0.215*  
                  (0.057)         (0.014)         (0.107)   
_cons               0.000          -0.052           0.000   
                      (.)         (0.037)             (.)   
------------------------------------------------------------
r2_w                0.008           0.006           0.035   
r2_b                0.183           0.628           0.333   
r2_o                0.009           0.012           0.037   
N                3249.000        2223.000        2907.000   
N_g                19.000          13.000          17.000   
------------------------------------------------------------
.   
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;NZ&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store B
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;RU&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store C  
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SE&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re  
.   estimates store D
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;SW&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store E
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;UK&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store F 
.   quietly xtreg D.gslmc c.neg##c.timesecStorylog c.neg##c.right2 order L.gslm
&gt; c female age income university if country2==&quot;US&quot; &amp; period==2 &amp; political_inte
&gt; rest_dichox==1, re   
.   estimates store G 
.   esttab B C D, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.007           0.014*          0.001   
                  (0.005)         (0.007)         (0.002)   
timesecSto~g       -0.012           0.017          -0.000   
                  (0.012)         (0.015)         (0.004)   
c.neg#c.ti~g       -0.003          -0.008**        -0.001   
                  (0.002)         (0.003)         (0.001)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2              0.023           0.018           0.009   
                  (0.030)         (0.031)         (0.011)   
c.neg#c.ri~2       -0.005          -0.001           0.000   
                  (0.006)         (0.006)         (0.002)   
order               0.000          -0.001           0.000   
                  (0.000)         (0.000)         (0.000)   
L.gslmc            -0.046***       -0.016*          0.010** 
                  (0.007)         (0.007)         (0.004)   
female             -0.003           0.012           0.003   
                  (0.007)         (0.007)         (0.002)   
age                -0.000          -0.000           0.000   
                  (0.000)         (0.000)         (0.000)   
income             -0.021          -0.028           0.009   
                  (0.013)         (0.017)         (0.008)   
university          0.011          -0.003           0.004   
                  (0.008)         (0.014)         (0.002)   
_cons               0.018          -0.012          -0.022   
                  (0.027)         (0.038)         (0.012)   
------------------------------------------------------------
r2_w                0.023           0.010           0.003   
r2_b                0.017           0.395           0.240   
r2_o                0.022           0.012           0.006   
N                3420.000        2736.000        4617.000   
N_g                20.000          16.000          27.000   
------------------------------------------------------------
.   esttab E F G, cells(b(star fmt(3)) se(par fmt(3))) nogaps stat(r2_w r2_b r2
&gt; _o N N_g) 

------------------------------------------------------------
                      (1)             (2)             (3)   
                  D.gslmc         D.gslmc         D.gslmc   
                     b/se            b/se            b/se   
------------------------------------------------------------
neg                 0.006           0.003           0.034*  
                  (0.004)         (0.004)         (0.013)   
timesecSto~g        0.003           0.005           0.056   
                  (0.011)         (0.010)         (0.035)   
c.neg#c.ti~g       -0.004          -0.003          -0.012   
                  (0.002)         (0.002)         (0.007)   
neg                 0.000           0.000           0.000   
                      (.)             (.)             (.)   
right2             -0.020          -0.012           0.163   
                  (0.024)         (0.029)         (0.093)   
c.neg#c.ri~2        0.004           0.005          -0.022   
                  (0.004)         (0.005)         (0.018)   
order              -0.000           0.000           0.001   
                  (0.000)         (0.000)         (0.001)   
L.gslmc            -0.015          -0.093***       -0.361***
                  (0.008)         (0.008)         (0.009)   
female             -0.002          -0.000           0.007   
                  (0.010)         (0.006)         (0.016)   
age                 0.000          -0.000          -0.001   
                  (0.000)         (0.000)         (0.001)   
income             -0.001          -0.006          -0.038   
                  (0.018)         (0.015)         (0.035)   
university         -0.004          -0.003           0.022   
                  (0.008)         (0.007)         (0.018)   
_cons              -0.004           0.003          -0.156*  
                  (0.025)         (0.023)         (0.076)   
------------------------------------------------------------
r2_w                0.011           0.053           0.173   
r2_b                0.205           0.298           0.005   
r2_o                0.011           0.055           0.166   
N                1872.000        2709.000        7520.000   
N_g                11.000          16.000          44.000   
------------------------------------------------------------</code></pre>
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</div>

<div id="rmd-source-code">---
title: "Negativity Biases and Political Ideology: A Comparative Test Across 17 Countries, Replication File"
output: html_notebook
---

The file that follows replicates all analyses in Patrick Fournier, Stuart Soroka and Lilach Nir (2020), Negativity Biases and Political Ideology: A Comparative Test Across 17 Countries, forthcoming in the American Political Science Review.  Analyses were done primiarly in STATA, with selected analyses for figures - and the figures themselves - drawn in R.  For this reason, we are distributing this RMarkdown file that pulls together all the various datasets and analyses.

The only graphic that is not produced using the distributed script is Figure 5, which offers descriptives for the IAPS pictures used in the study.  Those descriptives must be downloaded here: https://csea.phhp.ufl.edu.

There are five different datasets distributed with this RMarkdown file:

Sample-description.dta <- The respondent-level dataset including all responses, not just those with working physiological measures.

Individual-data.dta <- The working respondent-level dataset.

Stimulus-data.dta <- The respondent-stimulus-level panel dataset.

Time-series-data-photos.dta <- The times-series by-respondent panel dataset.

Time-series-data-videos.dta <- The times-series by-respondent panel dataset.

Analysis run in STATA are stored in STATA do-files with names that correspond to each of these datasets.  Those STATA do-files can be run in STATA, independent of this script.  Alternatively, the current file produces the figures alongside reading in and processing all of the STATA do-files using the RStata package.

## Setup

```{r setup}

rm(list=ls())

library(rio) ; library(plm) ; library(RStata) ; library(effects) ; library(knitr)
options("RStata.StataPath" = '/Applications/Stata/StataMP.app/Contents/MacOS/stata-mp')
options("RStata.StataVersion" = 15)

#setting countries
countries <- c("BR","CA.e","CA.f","CH","CN","DK","FR","GH","IN","IS.j","IS.p","IT","JP","NZ","RU","SE","SW","UK","US")
ncountries <- length(countries)

```

```{r datasets}

S1 <- import("Sample-description.dta") #respondent-level dataset
S1 <- S1[S1$country2!="",]
S <- import("Individual-data.dta") #respondent-level dataset
S <- S[S$country2!="",]
R <- import("Stimulus-data.dta") #respondent-level dataset
V <- import("Time-series-data-videos.dta") #respondent-level dataset
P <- import("Time-series-data-photos.dta") #respondent-level dataset

```

## Analysis of Sample-description.dta

```{r figure 1a}

TAB <- as.data.frame(table(S1$respnum))
TAB<- table(S1$female,S1$country2)
TAB <- TAB[1:2,ncountries:1]
{
pdf("figure.1a.pdf", width = 4, height = 6, bg="white") 
barplot(TAB, las=1, legend.text = c("Female", "Male"),args.legend = list(x = "right", bty = "n"), horiz=TRUE)
title(main="Respondent Sex")
title(xlab="Sample Size by Sex")
invisible(dev.off())
}

```

```{r figure 1b}

{
pdf("figure.1b.pdf", width = 4, height = 6, bg="white") 
plot(c(18,70),c(0,ncountries),ylim=c(.5,ncountries), ann=F,axes=F,type="n")
title(main="Respondent Age")
for (i in 1:ncountries) {
  Q <- quantile(S1$age[S1$country2==countries[i]],c(.25,.75),na.rm=T)
  arrows(Q[1],ncountries+1-i,Q[2],ncountries+1-i,code=3,length=.05,angle=90,col="gray")
}
for (i in 1:ncountries) {
  M <- mean(S1$age[S1$country2==countries[i]],na.rm=T) ; points(M,ncountries+1-i,pch=15,cex=1.2)
}
axis(1)
axis(2,at=c(1:ncountries),labels=rev(countries),las=1)
title(xlab="Age, in Years")
invisible(dev.off())
}

```

```{r figure 1c}

{
pdf("figure.1c.pdf", width = 4, height = 6, bg="white") 
plot(c(1,2,3,4,5,6,7),c(0,2,5,6,7,11,12),ylim=c(.5,ncountries), ann=F,axes=F,type="n")
title(main="English Proficiency")
for (i in 1:ncountries) {
  Q <- quantile(S1$english_prof[S1$country2==countries[i]],c(.25,.75),na.rm=T)
  arrows(Q[1],ncountries+1-i,Q[2],ncountries+1-i,code=3,length=.05,angle=90,col="gray")
}
for (i in 1:ncountries) {
  M <- mean(S1$english_prof[S1$country2==countries[i]]) ; points(M,ncountries+1-i,pch=15,cex=1.2)
}
axis(1)
axis(2,at=c(1:ncountries),labels=rev(countries),las=1)
title(xlab="English Proficiency")
invisible(dev.off())
}

```

```{r STATA sample-description analyses, as.is=T}

stata_src <- readLines("Sample-description.do")
stata(stata_src,data.in=S1)

```

## Analysis of Individual-data.dta

```{r Figure 2}

M <- S[,c("v_gslmc_11","v_gslmc_12","v_gslmc_13","v_gslmc_14")]
M <- rowMeans(M,na.rm=T)
S$mean.neg <- M

M <- S[,c("v_gslmc_15","v_gslmc_16","v_gslmc_17","v_gslmc_18")]
M <- rowMeans(M,na.rm=T)
S$mean.pos <- M

a1 <- S[,c("mean.neg","wp_right2_dichox")]
a1$tone <- "neg"
colnames(a1) <- c("gsl","lr","tone")
a2 <- S[,c("mean.pos","wp_right2_dichox")]
a2$tone <- "pos"
colnames(a2) <- c("gsl","lr","tone")
A <- rbind(a1,a2)
rm(a1,a2)
A$tone <- as.factor(A$tone)
A$lr <- as.factor(A$lr)

model1 <- lm(gsl ~ lr * tone, data=A)
eff1 <- effect("lr * tone",model1, typical=mean)
s <- cbind(eff1$x,fit=eff1$fit,lower=eff1$lower,higher=eff1$upper)
s <- s[order(s$lr,s$tone),]
s$range <- c(1,2,4,5)

{
pdf("figure2.pdf", width = 7, height = 5, bg="white") 
par(mar=c(5.1,6.1,1.1,2.1))
plot(s$range,s$fit,type="n",ann=F,axes=F,xlim=c(.5,5.5),ylim=c(-.16,.08))
arrows(s$range,s$low,s$range,s$high,angle=90,length=.05,code=3,col="gray",lwd=2,lty=1)
points(s$range,s$fit,pch=15,cex=1.5)
axis(1,col="white",at=c(1,2,4,5),labels=c("Negative\n Video","Positive\n Video","Negative\n Video", "Positive\n Video"))
axis(2,las=1)
mtext("Mean Normalized GSL",side=2,line=4)
mtext("Left-Leaning Participants              Right-Leaning Participants",side=1,line=3)
invisible(dev.off())
}

```

```{r Figure 6}

a1 <- S[,c("mean_ph_neg_all","wp_right2_dichox")]
a1$tone <- "neg"
colnames(a1) <- c("gsl","lr","tone")
a2 <- S[,c("mean_ph_pos_all","wp_right2_dichox")]
a2$tone <- "pos"
colnames(a2) <- c("gsl","lr","tone")
A <- rbind(a1,a2)
rm(a1,a2)
A$tone <- as.factor(A$tone)
A$lr <- as.factor(A$lr)

model1 <- lm(gsl ~ lr * tone, data=A)
eff1 <- effect("lr * tone",model1, typical=mean)
s <- cbind(eff1$x,fit=eff1$fit,lower=eff1$lower,higher=eff1$upper)
s <- s[order(s$lr,s$tone),]
s$range <- c(1,2,4,5)

{
pdf("figure6.pdf", width = 7, height = 5, bg="white") 
par(mar=c(5.1,6.1,1.1,2.1))
plot(s$range,s$fit,type="n",ann=F,axes=F,xlim=c(.5,5.5),ylim=c(-.05,.05))
arrows(s$range,s$low,s$range,s$high,angle=90,length=.05,code=3,col="gray",lwd=2,lty=1)
points(s$range,s$fit,pch=15,cex=1.5)
axis(1,col="white",at=c(1,2,4,5),labels=c("Negative\n Photos","Positive\n Photos","Negative\n Photos", "Positive\n Photos"))
axis(2,las=1)
mtext("Mean Normalized GSL",side=2,line=4)
mtext("Left-Leaning Participants              Right-Leaning Participants",side=1,line=3)
invisible(dev.off())
}

```

```{r Appendix Figure 1}

S$right <- NA
S$right[S$left_right2<.5] <- 0
S$right[S$left_right2==.5] <- .5
S$right[S$left_right2>.5] <- 1
tab <- RcmdrMisc::rowPercents(table(S$country2,S$right))
tab <- t(tab[,c(1:3)])
tab <- tab[,c(19:1)]

{
pdf("figureA1.pdf", width = 4, height = 6, bg="white") 
barplot(tab, las=1, legend.text = c("Left", "Center", "Right"),args.legend = list(x = "bottom", bty = "n", inset=c(0, -.23),ncol=3), horiz=TRUE)
mtext("% Participants by Ideological Category", side=1, line=2)
invisible(dev.off())
}

```

```{r STATA individual-data analyses, as.is=T}

stata_src <- readLines("Individual-data.do")
stata(stata_src,data.in=S)

```

## Analysis of Stimulus-data.dta

```{r Figure 3}

coefs <- as.data.frame(countries)
coefs$b <- NA
coefs$se <- NA
E <- R[R$stimtype=="single video" & R$local==0,]
E <- E[!is.na(E$vid_order),]
E$negativity <- E$v_negativity
Pd <- pdata.frame(E,index = c("resp", "vid_order"))
Pd$orderN <- as.numeric(Pd$vid_order)
for (i in countries){
  model <- plm(gslmc ~ negativity * wp_right2 + orderN + female + age + income + university,
               data=Pd[Pd$country2==i,], model="random")
  s <- summary(model)$coef
  coefs$b[coefs$countries==i] <- s[9,1]
  coefs$se[coefs$countries==i] <- s[9,2]
}
coefs$low <- coefs$b - (coefs$se * 1.96)
coefs$high <- coefs$b + (coefs$se * 1.96)
coefs$range <- as.numeric(rownames(coefs))

{
pdf("figure3.pdf", width = 10, height = 5, bg="white") 
par(mar=c(5.1,4.1,1.1,2.1))
plot(coefs$range,coefs$b,type="n",ann=F,axes=F,ylim=c(-1.5,1.5))
abline(h=0,lwd=1,lty=2,col="black")
arrows(coefs$range,coefs$low,coefs$range,coefs$high,angle=90,length=.05,code=3,col="gray",lwd=2,lty=1)
points(coefs$range,coefs$b,pch=15,cex=1.5)
axis(1,col="white",at=c(1:19),labels=coefs$countries,cex.axis=.8)
axis(2,las=1)
mtext("Ideological Difference in the Effect of Negativity",side=2,line=3)
invisible(dev.off())
}

```

```{r STATA stimulus-data analyses, as.is=T}

stata_src <- readLines("Stimulus-data.do")
stata(stata_src,data.in=R)

```

## Analysis of Time-series-data-videos.dta

```{r Figure 4}

coefs <- as.data.frame(countries)
coefs$b <- NA
coefs$se <- NA

#V$neg <- V$negativity
A <- V[V$period==2 & V$local==0,]

Pd <- pdata.frame(A,index = c("resp", "timesec"))
Pd$Lgslmc <- lag(Pd$gslmc,1)
Pd$Dgslmc <- Pd$gslmc - Pd$Lgslmc
for (i in countries){
model <- plm(Dgslmc ~ negativity * timesecStorylog + negativity * wp_right2  + Lgslmc 
             + female + age + income + university + order,
              data=Pd[Pd$country2==i,], model="random") 
  s <- summary(model)$coef
  coefs$b[coefs$countries==i] <- s[12,1]
  coefs$se[coefs$countries==i] <- s[12,2]
}

coefs$low <- coefs$b - (coefs$se * 1.96)
coefs$high <- coefs$b + (coefs$se * 1.96)
coefs$range <- as.numeric(rownames(coefs))

{
pdf("figure4.pdf", width = 10, height = 5, bg="white") 
par(mar=c(5.1,4.1,1.1,2.1))
plot(coefs$range,coefs$b,type="n",ann=F,axes=F,ylim=c(-.025,.025))
abline(h=0,lwd=1,lty=2,col="black")
arrows(coefs$range,coefs$low,coefs$range,coefs$high,angle=90,length=.05,code=3,col="gray",lwd=2,lty=1)
points(coefs$range,coefs$b,pch=15,cex=1.5)
axis(1,col="white",at=c(1:19),labels=coefs$countries,cex.axis=.8)
axis(2,las=1)
mtext("Ideological Difference in the Effect of Negativity",side=2,line=3.2)
invisible(dev.off())
}

```

```{r STATA time-series-data-videos analyses, as.is=T}

stata_src <- readLines("Time-series-data-videos.do")
stata(stata_src,data.in=V)

```

## Analysis of Time-series-data-photos.dta

```{r STATA time-series-data-photos analyses, as.is=T}

P$country2 <- as.character(P$country2)
stata_src <- readLines("Time-series-data-photos.do")
stata(stata_src,data.in=P)

```



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